{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# 时间序列（time series）\n",
    "时间序列（time series）数据是一种重要的结构化数据形式。时间序列数据的意义取决于具体的应用场景，主要有以下几种：\n",
    "* 时间戳（timestamp），特定的时刻。\n",
    "* 固定时期（period），如2007年1月或2010年全年。\n",
    "* 时间间隔（interval），由起始和结束时间戳表示。时期（period）可以被看做间隔（interval）的特例。\n",
    "* 实验或过程时间，每个时间点都是相对于特定起始时间的一个度量。例如，从放入烤箱时起，每秒钟饼干的直径。\n",
    "\n",
    "<br>\n",
    "pandas提供了许多内置的时间序列处理工具和数据算法。因此，你可以高效处理非常大的时间序列，轻松地进行切片/切块、聚合、对定期/不定期的时间序列进行重采样等。\n",
    "# 日期和时间数据类型及工具\n",
    "Python标准库包含用于日期（date）和时间（time）数据的数据类型，而且还有日历方面的功能。我们主要会用到datetime、time以及calendar模块。datetime.datetime（也可以简写为datetime）是用得最多的数据类型："
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "datetime.datetime(2018, 7, 28, 18, 7, 41, 940759)"
      ]
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "from datetime import datetime\n",
    "now=datetime.now()\n",
    "now"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(2018, 7, 28)"
      ]
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "now.year,now.month,now.day"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "datetime以毫秒形式存储日期和时间。timedelta表示两个datetime对象之间的时间差："
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [],
   "source": [
    "delta=datetime(2018,7,7,1,1,1)-datetime(2018,6,6,2,2,2)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(30, 82739, 0)"
      ]
     },
     "execution_count": 10,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "delta.days,delta.seconds,delta.microseconds"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "可以给datetime对象加上（或减去）一个或多个timedelta，这样会产生一个新对象："
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(datetime.datetime(2018, 8, 8, 0, 0), datetime.datetime(2018, 8, 20, 0, 0))"
      ]
     },
     "execution_count": 11,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "from datetime import timedelta\n",
    "start=datetime(2018,8,8)\n",
    "end=start+timedelta(12)\n",
    "start,end"
   ]
  },
  {
   "attachments": {
    "image.png": {
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"
    }
   },
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "datetime模块中的数据类型:\n",
    "![image.png](attachment:image.png)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# 字符串和datetime的相互转换"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "'2018-08-08 00:00:00'"
      ]
     },
     "execution_count": 12,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "dt=datetime(2018,8,8)\n",
    "str(dt)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "'2018/08/08'"
      ]
     },
     "execution_count": 14,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "dt.strftime('%Y/%m/%d')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "18                            -----%y 两位数的年份表示（00-99）\n",
      "2018                          -----%Y 四位数的年份表示（000-9999）\n",
      "07                            -----%m 月份（01-12）\n",
      "28                            -----%d 月内中的一天（0-31）\n",
      "18                            -----%H 24小时制小时数（0-23）\n",
      "06                            -----%I 12小时制小时数（01-12）\n",
      "30                            -----%M 分钟数（00=59）\n",
      "08                            -----%S 秒（00-59）\n",
      "Sat                           -----%a 本地简化星期名称\n",
      "Saturday                      -----%A 本地完整星期名称\n",
      "Jul                           -----%b 本地简化的月份名称\n",
      "July                          -----%B 本地完整的月份名称\n",
      "Sat Jul 28 18:30:08 2018      -----%c 本地相应的日期表示和时间表示\n",
      "209                           -----%j 年内的一天（001-366）\n",
      "PM                            -----%p 本地A.M.或P.M.的等价符\n",
      "29                            -----%U 一年中的星期数（00-53）星期天为星期的开始\n",
      "6                             -----%w 星期（0-6），星期天为星期的开始\n",
      "30                            -----%W 一年中的星期数（00-53）星期一为星期的开始\n",
      "07/28/18                      -----%x 本地相应的日期表示\n",
      "18:30:08                      -----%X 本地相应的时间表示\n",
      "                              -----%Z 当前时区的名称\n",
      "%                             -----%% %号本身\n"
     ]
    }
   ],
   "source": [
    "ls=[\"%y 两位数的年份表示（00-99）\"\n",
    ",\"%Y 四位数的年份表示（000-9999）\"\n",
    ",\"%m 月份（01-12）\"\n",
    ",\"%d 月内中的一天（0-31）\"\n",
    ",\"%H 24小时制小时数（0-23）\"\n",
    ",\"%I 12小时制小时数（01-12）\"\n",
    ",\"%M 分钟数（00=59）\"\n",
    ",\"%S 秒（00-59）\"\n",
    ",\"%a 本地简化星期名称\"\n",
    ",\"%A 本地完整星期名称\"\n",
    ",\"%b 本地简化的月份名称\"\n",
    ",\"%B 本地完整的月份名称\"\n",
    ",\"%c 本地相应的日期表示和时间表示\"\n",
    ",\"%j 年内的一天（001-366）\"\n",
    ",\"%p 本地A.M.或P.M.的等价符\"\n",
    ",\"%U 一年中的星期数（00-53）星期天为星期的开始\"\n",
    ",\"%w 星期（0-6），星期天为星期的开始\"\n",
    ",\"%W 一年中的星期数（00-53）星期一为星期的开始\"\n",
    ",\"%x 本地相应的日期表示\"\n",
    ",\"%X 本地相应的时间表示\"\n",
    ",\"%Z 当前时区的名称\"\n",
    ",\"%% %号本身\"]\n",
    "for i in ls:\n",
    "    print('{0:30}-----{1}'.format(datetime.now().strftime(i[:2]),i))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "datetime.datetime(2018, 8, 8, 0, 0)"
      ]
     },
     "execution_count": 16,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "datetime.strptime('2018-08-08','%Y-%m-%d')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "datetime.strptime是通过已知格式进行日期解析的最佳方式。但是每次都要编写格式定义是很麻烦的事情，尤其是对于一些常见的日期格式。这种情况下，你可以用dateutil这个第三方包中的parser.parse方法（pandas中已经自动安装好了）："
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "datetime.datetime(2018, 8, 18, 0, 0)"
      ]
     },
     "execution_count": 17,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "from dateutil.parser import parse\n",
    "parse('20180818')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "在国际通用的格式中，日出现在月的前面很普遍，传入dayfirst=True即可解决这个问题："
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "datetime.datetime(2011, 8, 6, 0, 0)"
      ]
     },
     "execution_count": 22,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "parse('06-08-11',dayfirst=True)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "pandas通常是用于处理成组日期的，不管这些日期是DataFrame的轴索引还是列。to_datetime方法可以解析多种不同的日期表示形式。"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "DatetimeIndex(['2017-07-07', '2018-08-08'], dtype='datetime64[ns]', freq=None)"
      ]
     },
     "execution_count": 25,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "import pandas as pd\n",
    "dts=['2017-07-07','2018-08-08']\n",
    "pd.to_datetime(dts)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "它还可以处理缺失值（None、空字符串等）："
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "DatetimeIndex(['2017-07-07', '2018-08-08', 'NaT'], dtype='datetime64[ns]', freq=None)"
      ]
     },
     "execution_count": 26,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "pd.to_datetime(dts+[None])"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "NaT（Not a Time）是pandas中时间戳数据的null值。<br>"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>date</th>\n",
       "      <th>open</th>\n",
       "      <th>close</th>\n",
       "      <th>high</th>\n",
       "      <th>low</th>\n",
       "      <th>volume</th>\n",
       "      <th>code</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>134</th>\n",
       "      <td>2018-07-23</td>\n",
       "      <td>736.00</td>\n",
       "      <td>732.07</td>\n",
       "      <td>741.15</td>\n",
       "      <td>720.01</td>\n",
       "      <td>35969.0</td>\n",
       "      <td>600519</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>135</th>\n",
       "      <td>2018-07-24</td>\n",
       "      <td>732.68</td>\n",
       "      <td>745.40</td>\n",
       "      <td>747.30</td>\n",
       "      <td>723.00</td>\n",
       "      <td>41808.0</td>\n",
       "      <td>600519</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>136</th>\n",
       "      <td>2018-07-25</td>\n",
       "      <td>746.95</td>\n",
       "      <td>743.81</td>\n",
       "      <td>749.88</td>\n",
       "      <td>740.01</td>\n",
       "      <td>21743.0</td>\n",
       "      <td>600519</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>137</th>\n",
       "      <td>2018-07-26</td>\n",
       "      <td>748.90</td>\n",
       "      <td>735.62</td>\n",
       "      <td>748.90</td>\n",
       "      <td>734.23</td>\n",
       "      <td>23067.0</td>\n",
       "      <td>600519</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>138</th>\n",
       "      <td>2018-07-27</td>\n",
       "      <td>736.00</td>\n",
       "      <td>738.56</td>\n",
       "      <td>744.30</td>\n",
       "      <td>730.00</td>\n",
       "      <td>20913.0</td>\n",
       "      <td>600519</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "           date    open   close    high     low   volume    code\n",
       "134  2018-07-23  736.00  732.07  741.15  720.01  35969.0  600519\n",
       "135  2018-07-24  732.68  745.40  747.30  723.00  41808.0  600519\n",
       "136  2018-07-25  746.95  743.81  749.88  740.01  21743.0  600519\n",
       "137  2018-07-26  748.90  735.62  748.90  734.23  23067.0  600519\n",
       "138  2018-07-27  736.00  738.56  744.30  730.00  20913.0  600519"
      ]
     },
     "execution_count": 28,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "import tushare as ts\n",
    "df=ts.get_k_data('600519',start='2018-05-05')\n",
    "df.tail()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 29,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "str"
      ]
     },
     "execution_count": 29,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "type(df.iloc[0,0])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 30,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "134   2018-07-23\n",
       "135   2018-07-24\n",
       "136   2018-07-25\n",
       "137   2018-07-26\n",
       "138   2018-07-27\n",
       "Name: date, dtype: datetime64[ns]"
      ]
     },
     "execution_count": 30,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "pd.to_datetime(df.date).tail()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 31,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
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       "\n",
       "    .dataframe tbody tr th {\n",
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       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>date</th>\n",
       "      <th>open</th>\n",
       "      <th>close</th>\n",
       "      <th>high</th>\n",
       "      <th>low</th>\n",
       "      <th>volume</th>\n",
       "      <th>code</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>134</th>\n",
       "      <td>2018-07-23</td>\n",
       "      <td>736.00</td>\n",
       "      <td>732.07</td>\n",
       "      <td>741.15</td>\n",
       "      <td>720.01</td>\n",
       "      <td>35969.0</td>\n",
       "      <td>600519</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>135</th>\n",
       "      <td>2018-07-24</td>\n",
       "      <td>732.68</td>\n",
       "      <td>745.40</td>\n",
       "      <td>747.30</td>\n",
       "      <td>723.00</td>\n",
       "      <td>41808.0</td>\n",
       "      <td>600519</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>136</th>\n",
       "      <td>2018-07-25</td>\n",
       "      <td>746.95</td>\n",
       "      <td>743.81</td>\n",
       "      <td>749.88</td>\n",
       "      <td>740.01</td>\n",
       "      <td>21743.0</td>\n",
       "      <td>600519</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>137</th>\n",
       "      <td>2018-07-26</td>\n",
       "      <td>748.90</td>\n",
       "      <td>735.62</td>\n",
       "      <td>748.90</td>\n",
       "      <td>734.23</td>\n",
       "      <td>23067.0</td>\n",
       "      <td>600519</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>138</th>\n",
       "      <td>2018-07-27</td>\n",
       "      <td>736.00</td>\n",
       "      <td>738.56</td>\n",
       "      <td>744.30</td>\n",
       "      <td>730.00</td>\n",
       "      <td>20913.0</td>\n",
       "      <td>600519</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "          date    open   close    high     low   volume    code\n",
       "134 2018-07-23  736.00  732.07  741.15  720.01  35969.0  600519\n",
       "135 2018-07-24  732.68  745.40  747.30  723.00  41808.0  600519\n",
       "136 2018-07-25  746.95  743.81  749.88  740.01  21743.0  600519\n",
       "137 2018-07-26  748.90  735.62  748.90  734.23  23067.0  600519\n",
       "138 2018-07-27  736.00  738.56  744.30  730.00  20913.0  600519"
      ]
     },
     "execution_count": 31,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.date=pd.to_datetime(df.date)\n",
    "df.tail()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 32,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "date      datetime64[ns]\n",
       "open             float64\n",
       "close            float64\n",
       "high             float64\n",
       "low              float64\n",
       "volume           float64\n",
       "code              object\n",
       "dtype: object"
      ]
     },
     "execution_count": 32,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.dtypes"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 33,
   "metadata": {},
   "outputs": [],
   "source": [
    "df.set_index(keys=['date'],inplace=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 34,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>open</th>\n",
       "      <th>close</th>\n",
       "      <th>high</th>\n",
       "      <th>low</th>\n",
       "      <th>volume</th>\n",
       "      <th>code</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>date</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>2018-07-23</th>\n",
       "      <td>736.00</td>\n",
       "      <td>732.07</td>\n",
       "      <td>741.15</td>\n",
       "      <td>720.01</td>\n",
       "      <td>35969.0</td>\n",
       "      <td>600519</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2018-07-24</th>\n",
       "      <td>732.68</td>\n",
       "      <td>745.40</td>\n",
       "      <td>747.30</td>\n",
       "      <td>723.00</td>\n",
       "      <td>41808.0</td>\n",
       "      <td>600519</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2018-07-25</th>\n",
       "      <td>746.95</td>\n",
       "      <td>743.81</td>\n",
       "      <td>749.88</td>\n",
       "      <td>740.01</td>\n",
       "      <td>21743.0</td>\n",
       "      <td>600519</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2018-07-26</th>\n",
       "      <td>748.90</td>\n",
       "      <td>735.62</td>\n",
       "      <td>748.90</td>\n",
       "      <td>734.23</td>\n",
       "      <td>23067.0</td>\n",
       "      <td>600519</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2018-07-27</th>\n",
       "      <td>736.00</td>\n",
       "      <td>738.56</td>\n",
       "      <td>744.30</td>\n",
       "      <td>730.00</td>\n",
       "      <td>20913.0</td>\n",
       "      <td>600519</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "              open   close    high     low   volume    code\n",
       "date                                                       \n",
       "2018-07-23  736.00  732.07  741.15  720.01  35969.0  600519\n",
       "2018-07-24  732.68  745.40  747.30  723.00  41808.0  600519\n",
       "2018-07-25  746.95  743.81  749.88  740.01  21743.0  600519\n",
       "2018-07-26  748.90  735.62  748.90  734.23  23067.0  600519\n",
       "2018-07-27  736.00  738.56  744.30  730.00  20913.0  600519"
      ]
     },
     "execution_count": 34,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.tail()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 36,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "DatetimeIndex(['2018-05-07', '2018-05-08', '2018-05-09', '2018-05-10',\n",
       "               '2018-05-11', '2018-05-14', '2018-05-15', '2018-05-16',\n",
       "               '2018-05-17', '2018-05-18', '2018-05-21', '2018-05-22',\n",
       "               '2018-05-23', '2018-05-24', '2018-05-25', '2018-05-28',\n",
       "               '2018-05-29', '2018-05-30', '2018-05-31', '2018-06-01',\n",
       "               '2018-06-04', '2018-06-05', '2018-06-06', '2018-06-07',\n",
       "               '2018-06-08', '2018-06-11', '2018-06-12', '2018-06-13',\n",
       "               '2018-06-14', '2018-06-15', '2018-06-19', '2018-06-20',\n",
       "               '2018-06-21', '2018-06-22', '2018-06-25', '2018-06-26',\n",
       "               '2018-06-27', '2018-06-28', '2018-06-29', '2018-07-02',\n",
       "               '2018-07-03', '2018-07-04', '2018-07-05', '2018-07-06',\n",
       "               '2018-07-09', '2018-07-10', '2018-07-11', '2018-07-12',\n",
       "               '2018-07-13', '2018-07-16', '2018-07-17', '2018-07-18',\n",
       "               '2018-07-19', '2018-07-20', '2018-07-23', '2018-07-24',\n",
       "               '2018-07-25', '2018-07-26', '2018-07-27'],\n",
       "              dtype='datetime64[ns]', name='date', freq=None)"
      ]
     },
     "execution_count": 36,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.index"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# 索引、选取、子集构造\n",
    "当你根据标签索引选取数据时，时间序列和其它的pandas.Series很像："
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 37,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "open         736\n",
       "close     738.56\n",
       "high       744.3\n",
       "low          730\n",
       "volume     20913\n",
       "code      600519\n",
       "Name: 2018-07-27 00:00:00, dtype: object"
      ]
     },
     "execution_count": 37,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.loc[df.index[-1],:]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 43,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "open       748.9\n",
       "close     735.62\n",
       "high       748.9\n",
       "low       734.23\n",
       "volume     23067\n",
       "code      600519\n",
       "Name: 2018-07-26 00:00:00, dtype: object"
      ]
     },
     "execution_count": 43,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.loc['26-07-2018',:]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 46,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
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       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>open</th>\n",
       "      <th>close</th>\n",
       "      <th>high</th>\n",
       "      <th>low</th>\n",
       "      <th>volume</th>\n",
       "      <th>code</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>date</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>2018-07-02</th>\n",
       "      <td>734.52</td>\n",
       "      <td>711.55</td>\n",
       "      <td>739.33</td>\n",
       "      <td>703.00</td>\n",
       "      <td>37558.0</td>\n",
       "      <td>600519</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2018-07-03</th>\n",
       "      <td>709.76</td>\n",
       "      <td>694.92</td>\n",
       "      <td>715.78</td>\n",
       "      <td>678.23</td>\n",
       "      <td>82837.0</td>\n",
       "      <td>600519</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2018-07-04</th>\n",
       "      <td>692.00</td>\n",
       "      <td>690.91</td>\n",
       "      <td>700.00</td>\n",
       "      <td>688.00</td>\n",
       "      <td>37990.0</td>\n",
       "      <td>600519</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2018-07-05</th>\n",
       "      <td>700.00</td>\n",
       "      <td>702.39</td>\n",
       "      <td>716.20</td>\n",
       "      <td>700.00</td>\n",
       "      <td>47123.0</td>\n",
       "      <td>600519</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2018-07-06</th>\n",
       "      <td>707.00</td>\n",
       "      <td>714.12</td>\n",
       "      <td>720.93</td>\n",
       "      <td>699.26</td>\n",
       "      <td>44156.0</td>\n",
       "      <td>600519</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2018-07-09</th>\n",
       "      <td>720.03</td>\n",
       "      <td>727.24</td>\n",
       "      <td>729.86</td>\n",
       "      <td>719.73</td>\n",
       "      <td>40572.0</td>\n",
       "      <td>600519</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2018-07-10</th>\n",
       "      <td>729.00</td>\n",
       "      <td>725.76</td>\n",
       "      <td>731.50</td>\n",
       "      <td>713.33</td>\n",
       "      <td>29010.0</td>\n",
       "      <td>600519</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2018-07-11</th>\n",
       "      <td>710.00</td>\n",
       "      <td>719.58</td>\n",
       "      <td>724.00</td>\n",
       "      <td>702.22</td>\n",
       "      <td>24278.0</td>\n",
       "      <td>600519</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2018-07-12</th>\n",
       "      <td>718.00</td>\n",
       "      <td>737.54</td>\n",
       "      <td>741.17</td>\n",
       "      <td>718.00</td>\n",
       "      <td>40170.0</td>\n",
       "      <td>600519</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2018-07-13</th>\n",
       "      <td>742.30</td>\n",
       "      <td>746.99</td>\n",
       "      <td>748.10</td>\n",
       "      <td>735.12</td>\n",
       "      <td>28907.0</td>\n",
       "      <td>600519</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2018-07-16</th>\n",
       "      <td>752.30</td>\n",
       "      <td>754.68</td>\n",
       "      <td>764.11</td>\n",
       "      <td>751.03</td>\n",
       "      <td>32474.0</td>\n",
       "      <td>600519</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2018-07-17</th>\n",
       "      <td>757.00</td>\n",
       "      <td>742.43</td>\n",
       "      <td>757.00</td>\n",
       "      <td>736.02</td>\n",
       "      <td>27806.0</td>\n",
       "      <td>600519</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2018-07-18</th>\n",
       "      <td>742.43</td>\n",
       "      <td>737.44</td>\n",
       "      <td>749.69</td>\n",
       "      <td>735.00</td>\n",
       "      <td>24521.0</td>\n",
       "      <td>600519</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2018-07-19</th>\n",
       "      <td>739.00</td>\n",
       "      <td>740.95</td>\n",
       "      <td>743.95</td>\n",
       "      <td>735.02</td>\n",
       "      <td>18078.0</td>\n",
       "      <td>600519</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2018-07-20</th>\n",
       "      <td>741.50</td>\n",
       "      <td>741.13</td>\n",
       "      <td>743.13</td>\n",
       "      <td>728.00</td>\n",
       "      <td>30548.0</td>\n",
       "      <td>600519</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2018-07-23</th>\n",
       "      <td>736.00</td>\n",
       "      <td>732.07</td>\n",
       "      <td>741.15</td>\n",
       "      <td>720.01</td>\n",
       "      <td>35969.0</td>\n",
       "      <td>600519</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2018-07-24</th>\n",
       "      <td>732.68</td>\n",
       "      <td>745.40</td>\n",
       "      <td>747.30</td>\n",
       "      <td>723.00</td>\n",
       "      <td>41808.0</td>\n",
       "      <td>600519</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2018-07-25</th>\n",
       "      <td>746.95</td>\n",
       "      <td>743.81</td>\n",
       "      <td>749.88</td>\n",
       "      <td>740.01</td>\n",
       "      <td>21743.0</td>\n",
       "      <td>600519</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2018-07-26</th>\n",
       "      <td>748.90</td>\n",
       "      <td>735.62</td>\n",
       "      <td>748.90</td>\n",
       "      <td>734.23</td>\n",
       "      <td>23067.0</td>\n",
       "      <td>600519</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2018-07-27</th>\n",
       "      <td>736.00</td>\n",
       "      <td>738.56</td>\n",
       "      <td>744.30</td>\n",
       "      <td>730.00</td>\n",
       "      <td>20913.0</td>\n",
       "      <td>600519</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "              open   close    high     low   volume    code\n",
       "date                                                       \n",
       "2018-07-02  734.52  711.55  739.33  703.00  37558.0  600519\n",
       "2018-07-03  709.76  694.92  715.78  678.23  82837.0  600519\n",
       "2018-07-04  692.00  690.91  700.00  688.00  37990.0  600519\n",
       "2018-07-05  700.00  702.39  716.20  700.00  47123.0  600519\n",
       "2018-07-06  707.00  714.12  720.93  699.26  44156.0  600519\n",
       "2018-07-09  720.03  727.24  729.86  719.73  40572.0  600519\n",
       "2018-07-10  729.00  725.76  731.50  713.33  29010.0  600519\n",
       "2018-07-11  710.00  719.58  724.00  702.22  24278.0  600519\n",
       "2018-07-12  718.00  737.54  741.17  718.00  40170.0  600519\n",
       "2018-07-13  742.30  746.99  748.10  735.12  28907.0  600519\n",
       "2018-07-16  752.30  754.68  764.11  751.03  32474.0  600519\n",
       "2018-07-17  757.00  742.43  757.00  736.02  27806.0  600519\n",
       "2018-07-18  742.43  737.44  749.69  735.00  24521.0  600519\n",
       "2018-07-19  739.00  740.95  743.95  735.02  18078.0  600519\n",
       "2018-07-20  741.50  741.13  743.13  728.00  30548.0  600519\n",
       "2018-07-23  736.00  732.07  741.15  720.01  35969.0  600519\n",
       "2018-07-24  732.68  745.40  747.30  723.00  41808.0  600519\n",
       "2018-07-25  746.95  743.81  749.88  740.01  21743.0  600519\n",
       "2018-07-26  748.90  735.62  748.90  734.23  23067.0  600519\n",
       "2018-07-27  736.00  738.56  744.30  730.00  20913.0  600519"
      ]
     },
     "execution_count": 46,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.loc['2018-7',:]#获得指定月份的切片数据"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 47,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
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       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>open</th>\n",
       "      <th>close</th>\n",
       "      <th>high</th>\n",
       "      <th>low</th>\n",
       "      <th>volume</th>\n",
       "      <th>code</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>date</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>2018-05-07</th>\n",
       "      <td>650.711</td>\n",
       "      <td>688.396</td>\n",
       "      <td>692.054</td>\n",
       "      <td>648.561</td>\n",
       "      <td>85591.0</td>\n",
       "      <td>600519</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2018-05-08</th>\n",
       "      <td>688.258</td>\n",
       "      <td>698.906</td>\n",
       "      <td>702.160</td>\n",
       "      <td>688.258</td>\n",
       "      <td>62497.0</td>\n",
       "      <td>600519</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2018-05-09</th>\n",
       "      <td>699.153</td>\n",
       "      <td>692.123</td>\n",
       "      <td>702.328</td>\n",
       "      <td>687.360</td>\n",
       "      <td>32331.0</td>\n",
       "      <td>600519</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2018-05-10</th>\n",
       "      <td>693.651</td>\n",
       "      <td>704.191</td>\n",
       "      <td>705.976</td>\n",
       "      <td>693.651</td>\n",
       "      <td>39293.0</td>\n",
       "      <td>600519</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2018-05-11</th>\n",
       "      <td>708.628</td>\n",
       "      <td>707.968</td>\n",
       "      <td>720.273</td>\n",
       "      <td>705.680</td>\n",
       "      <td>39141.0</td>\n",
       "      <td>600519</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2018-05-14</th>\n",
       "      <td>713.864</td>\n",
       "      <td>732.016</td>\n",
       "      <td>732.598</td>\n",
       "      <td>713.864</td>\n",
       "      <td>51014.0</td>\n",
       "      <td>600519</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2018-05-15</th>\n",
       "      <td>735.556</td>\n",
       "      <td>732.657</td>\n",
       "      <td>735.990</td>\n",
       "      <td>723.724</td>\n",
       "      <td>38055.0</td>\n",
       "      <td>600519</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2018-05-16</th>\n",
       "      <td>729.640</td>\n",
       "      <td>724.237</td>\n",
       "      <td>735.221</td>\n",
       "      <td>723.014</td>\n",
       "      <td>30795.0</td>\n",
       "      <td>600519</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2018-05-17</th>\n",
       "      <td>724.828</td>\n",
       "      <td>717.197</td>\n",
       "      <td>727.175</td>\n",
       "      <td>713.864</td>\n",
       "      <td>28517.0</td>\n",
       "      <td>600519</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2018-05-18</th>\n",
       "      <td>713.854</td>\n",
       "      <td>728.970</td>\n",
       "      <td>730.626</td>\n",
       "      <td>711.093</td>\n",
       "      <td>29255.0</td>\n",
       "      <td>600519</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2018-05-21</th>\n",
       "      <td>733.584</td>\n",
       "      <td>724.533</td>\n",
       "      <td>736.838</td>\n",
       "      <td>722.225</td>\n",
       "      <td>29059.0</td>\n",
       "      <td>600519</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2018-05-22</th>\n",
       "      <td>724.927</td>\n",
       "      <td>729.216</td>\n",
       "      <td>729.482</td>\n",
       "      <td>719.800</td>\n",
       "      <td>16998.0</td>\n",
       "      <td>600519</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2018-05-23</th>\n",
       "      <td>729.640</td>\n",
       "      <td>713.647</td>\n",
       "      <td>729.640</td>\n",
       "      <td>713.450</td>\n",
       "      <td>28268.0</td>\n",
       "      <td>600519</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2018-05-24</th>\n",
       "      <td>709.920</td>\n",
       "      <td>705.384</td>\n",
       "      <td>718.459</td>\n",
       "      <td>703.018</td>\n",
       "      <td>30416.0</td>\n",
       "      <td>600519</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2018-05-25</th>\n",
       "      <td>702.032</td>\n",
       "      <td>706.824</td>\n",
       "      <td>716.822</td>\n",
       "      <td>702.032</td>\n",
       "      <td>26511.0</td>\n",
       "      <td>600519</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2018-05-28</th>\n",
       "      <td>707.948</td>\n",
       "      <td>730.034</td>\n",
       "      <td>730.291</td>\n",
       "      <td>705.108</td>\n",
       "      <td>42805.0</td>\n",
       "      <td>600519</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2018-05-29</th>\n",
       "      <td>728.457</td>\n",
       "      <td>721.190</td>\n",
       "      <td>739.500</td>\n",
       "      <td>721.042</td>\n",
       "      <td>40820.0</td>\n",
       "      <td>600519</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2018-05-30</th>\n",
       "      <td>717.039</td>\n",
       "      <td>715.708</td>\n",
       "      <td>726.978</td>\n",
       "      <td>709.969</td>\n",
       "      <td>37147.0</td>\n",
       "      <td>600519</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2018-05-31</th>\n",
       "      <td>720.027</td>\n",
       "      <td>740.614</td>\n",
       "      <td>741.097</td>\n",
       "      <td>720.017</td>\n",
       "      <td>71852.0</td>\n",
       "      <td>600519</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2018-06-01</th>\n",
       "      <td>740.614</td>\n",
       "      <td>734.679</td>\n",
       "      <td>744.410</td>\n",
       "      <td>728.417</td>\n",
       "      <td>36177.0</td>\n",
       "      <td>600519</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2018-06-04</th>\n",
       "      <td>741.817</td>\n",
       "      <td>771.022</td>\n",
       "      <td>771.939</td>\n",
       "      <td>735.438</td>\n",
       "      <td>73805.0</td>\n",
       "      <td>600519</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2018-06-05</th>\n",
       "      <td>775.489</td>\n",
       "      <td>777.017</td>\n",
       "      <td>783.574</td>\n",
       "      <td>766.349</td>\n",
       "      <td>52629.0</td>\n",
       "      <td>600519</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2018-06-06</th>\n",
       "      <td>776.968</td>\n",
       "      <td>774.750</td>\n",
       "      <td>789.737</td>\n",
       "      <td>771.348</td>\n",
       "      <td>48969.0</td>\n",
       "      <td>600519</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2018-06-07</th>\n",
       "      <td>778.920</td>\n",
       "      <td>770.036</td>\n",
       "      <td>784.412</td>\n",
       "      <td>767.995</td>\n",
       "      <td>39167.0</td>\n",
       "      <td>600519</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2018-06-08</th>\n",
       "      <td>769.080</td>\n",
       "      <td>767.059</td>\n",
       "      <td>774.897</td>\n",
       "      <td>759.220</td>\n",
       "      <td>34958.0</td>\n",
       "      <td>600519</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2018-06-11</th>\n",
       "      <td>765.185</td>\n",
       "      <td>764.870</td>\n",
       "      <td>774.996</td>\n",
       "      <td>757.573</td>\n",
       "      <td>36547.0</td>\n",
       "      <td>600519</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2018-06-12</th>\n",
       "      <td>767.108</td>\n",
       "      <td>788.001</td>\n",
       "      <td>792.251</td>\n",
       "      <td>765.629</td>\n",
       "      <td>55287.0</td>\n",
       "      <td>600519</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2018-06-13</th>\n",
       "      <td>788.800</td>\n",
       "      <td>779.265</td>\n",
       "      <td>791.383</td>\n",
       "      <td>777.836</td>\n",
       "      <td>35244.0</td>\n",
       "      <td>600519</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2018-06-14</th>\n",
       "      <td>778.940</td>\n",
       "      <td>775.124</td>\n",
       "      <td>782.687</td>\n",
       "      <td>764.328</td>\n",
       "      <td>36159.0</td>\n",
       "      <td>600519</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2018-06-15</th>\n",
       "      <td>773.200</td>\n",
       "      <td>773.330</td>\n",
       "      <td>778.580</td>\n",
       "      <td>769.100</td>\n",
       "      <td>31707.0</td>\n",
       "      <td>600519</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2018-06-19</th>\n",
       "      <td>769.000</td>\n",
       "      <td>738.000</td>\n",
       "      <td>769.000</td>\n",
       "      <td>737.000</td>\n",
       "      <td>60195.0</td>\n",
       "      <td>600519</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2018-06-20</th>\n",
       "      <td>741.000</td>\n",
       "      <td>763.590</td>\n",
       "      <td>765.000</td>\n",
       "      <td>741.000</td>\n",
       "      <td>45838.0</td>\n",
       "      <td>600519</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2018-06-21</th>\n",
       "      <td>765.220</td>\n",
       "      <td>759.320</td>\n",
       "      <td>778.890</td>\n",
       "      <td>758.770</td>\n",
       "      <td>39182.0</td>\n",
       "      <td>600519</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2018-06-22</th>\n",
       "      <td>754.000</td>\n",
       "      <td>766.530</td>\n",
       "      <td>767.000</td>\n",
       "      <td>750.000</td>\n",
       "      <td>28854.0</td>\n",
       "      <td>600519</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2018-06-25</th>\n",
       "      <td>766.000</td>\n",
       "      <td>765.560</td>\n",
       "      <td>778.970</td>\n",
       "      <td>764.900</td>\n",
       "      <td>32934.0</td>\n",
       "      <td>600519</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2018-06-26</th>\n",
       "      <td>765.310</td>\n",
       "      <td>754.800</td>\n",
       "      <td>769.880</td>\n",
       "      <td>747.000</td>\n",
       "      <td>46577.0</td>\n",
       "      <td>600519</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2018-06-27</th>\n",
       "      <td>752.000</td>\n",
       "      <td>722.440</td>\n",
       "      <td>757.000</td>\n",
       "      <td>721.000</td>\n",
       "      <td>57298.0</td>\n",
       "      <td>600519</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2018-06-28</th>\n",
       "      <td>714.000</td>\n",
       "      <td>710.930</td>\n",
       "      <td>719.000</td>\n",
       "      <td>697.000</td>\n",
       "      <td>50833.0</td>\n",
       "      <td>600519</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2018-06-29</th>\n",
       "      <td>712.300</td>\n",
       "      <td>731.460</td>\n",
       "      <td>732.300</td>\n",
       "      <td>705.000</td>\n",
       "      <td>32929.0</td>\n",
       "      <td>600519</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2018-07-02</th>\n",
       "      <td>734.520</td>\n",
       "      <td>711.550</td>\n",
       "      <td>739.330</td>\n",
       "      <td>703.000</td>\n",
       "      <td>37558.0</td>\n",
       "      <td>600519</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2018-07-03</th>\n",
       "      <td>709.760</td>\n",
       "      <td>694.920</td>\n",
       "      <td>715.780</td>\n",
       "      <td>678.230</td>\n",
       "      <td>82837.0</td>\n",
       "      <td>600519</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2018-07-04</th>\n",
       "      <td>692.000</td>\n",
       "      <td>690.910</td>\n",
       "      <td>700.000</td>\n",
       "      <td>688.000</td>\n",
       "      <td>37990.0</td>\n",
       "      <td>600519</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2018-07-05</th>\n",
       "      <td>700.000</td>\n",
       "      <td>702.390</td>\n",
       "      <td>716.200</td>\n",
       "      <td>700.000</td>\n",
       "      <td>47123.0</td>\n",
       "      <td>600519</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2018-07-06</th>\n",
       "      <td>707.000</td>\n",
       "      <td>714.120</td>\n",
       "      <td>720.930</td>\n",
       "      <td>699.260</td>\n",
       "      <td>44156.0</td>\n",
       "      <td>600519</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2018-07-09</th>\n",
       "      <td>720.030</td>\n",
       "      <td>727.240</td>\n",
       "      <td>729.860</td>\n",
       "      <td>719.730</td>\n",
       "      <td>40572.0</td>\n",
       "      <td>600519</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2018-07-10</th>\n",
       "      <td>729.000</td>\n",
       "      <td>725.760</td>\n",
       "      <td>731.500</td>\n",
       "      <td>713.330</td>\n",
       "      <td>29010.0</td>\n",
       "      <td>600519</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2018-07-11</th>\n",
       "      <td>710.000</td>\n",
       "      <td>719.580</td>\n",
       "      <td>724.000</td>\n",
       "      <td>702.220</td>\n",
       "      <td>24278.0</td>\n",
       "      <td>600519</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2018-07-12</th>\n",
       "      <td>718.000</td>\n",
       "      <td>737.540</td>\n",
       "      <td>741.170</td>\n",
       "      <td>718.000</td>\n",
       "      <td>40170.0</td>\n",
       "      <td>600519</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2018-07-13</th>\n",
       "      <td>742.300</td>\n",
       "      <td>746.990</td>\n",
       "      <td>748.100</td>\n",
       "      <td>735.120</td>\n",
       "      <td>28907.0</td>\n",
       "      <td>600519</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2018-07-16</th>\n",
       "      <td>752.300</td>\n",
       "      <td>754.680</td>\n",
       "      <td>764.110</td>\n",
       "      <td>751.030</td>\n",
       "      <td>32474.0</td>\n",
       "      <td>600519</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2018-07-17</th>\n",
       "      <td>757.000</td>\n",
       "      <td>742.430</td>\n",
       "      <td>757.000</td>\n",
       "      <td>736.020</td>\n",
       "      <td>27806.0</td>\n",
       "      <td>600519</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2018-07-18</th>\n",
       "      <td>742.430</td>\n",
       "      <td>737.440</td>\n",
       "      <td>749.690</td>\n",
       "      <td>735.000</td>\n",
       "      <td>24521.0</td>\n",
       "      <td>600519</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2018-07-19</th>\n",
       "      <td>739.000</td>\n",
       "      <td>740.950</td>\n",
       "      <td>743.950</td>\n",
       "      <td>735.020</td>\n",
       "      <td>18078.0</td>\n",
       "      <td>600519</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2018-07-20</th>\n",
       "      <td>741.500</td>\n",
       "      <td>741.130</td>\n",
       "      <td>743.130</td>\n",
       "      <td>728.000</td>\n",
       "      <td>30548.0</td>\n",
       "      <td>600519</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2018-07-23</th>\n",
       "      <td>736.000</td>\n",
       "      <td>732.070</td>\n",
       "      <td>741.150</td>\n",
       "      <td>720.010</td>\n",
       "      <td>35969.0</td>\n",
       "      <td>600519</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2018-07-24</th>\n",
       "      <td>732.680</td>\n",
       "      <td>745.400</td>\n",
       "      <td>747.300</td>\n",
       "      <td>723.000</td>\n",
       "      <td>41808.0</td>\n",
       "      <td>600519</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2018-07-25</th>\n",
       "      <td>746.950</td>\n",
       "      <td>743.810</td>\n",
       "      <td>749.880</td>\n",
       "      <td>740.010</td>\n",
       "      <td>21743.0</td>\n",
       "      <td>600519</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2018-07-26</th>\n",
       "      <td>748.900</td>\n",
       "      <td>735.620</td>\n",
       "      <td>748.900</td>\n",
       "      <td>734.230</td>\n",
       "      <td>23067.0</td>\n",
       "      <td>600519</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2018-07-27</th>\n",
       "      <td>736.000</td>\n",
       "      <td>738.560</td>\n",
       "      <td>744.300</td>\n",
       "      <td>730.000</td>\n",
       "      <td>20913.0</td>\n",
       "      <td>600519</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "               open    close     high      low   volume    code\n",
       "date                                                           \n",
       "2018-05-07  650.711  688.396  692.054  648.561  85591.0  600519\n",
       "2018-05-08  688.258  698.906  702.160  688.258  62497.0  600519\n",
       "2018-05-09  699.153  692.123  702.328  687.360  32331.0  600519\n",
       "2018-05-10  693.651  704.191  705.976  693.651  39293.0  600519\n",
       "2018-05-11  708.628  707.968  720.273  705.680  39141.0  600519\n",
       "2018-05-14  713.864  732.016  732.598  713.864  51014.0  600519\n",
       "2018-05-15  735.556  732.657  735.990  723.724  38055.0  600519\n",
       "2018-05-16  729.640  724.237  735.221  723.014  30795.0  600519\n",
       "2018-05-17  724.828  717.197  727.175  713.864  28517.0  600519\n",
       "2018-05-18  713.854  728.970  730.626  711.093  29255.0  600519\n",
       "2018-05-21  733.584  724.533  736.838  722.225  29059.0  600519\n",
       "2018-05-22  724.927  729.216  729.482  719.800  16998.0  600519\n",
       "2018-05-23  729.640  713.647  729.640  713.450  28268.0  600519\n",
       "2018-05-24  709.920  705.384  718.459  703.018  30416.0  600519\n",
       "2018-05-25  702.032  706.824  716.822  702.032  26511.0  600519\n",
       "2018-05-28  707.948  730.034  730.291  705.108  42805.0  600519\n",
       "2018-05-29  728.457  721.190  739.500  721.042  40820.0  600519\n",
       "2018-05-30  717.039  715.708  726.978  709.969  37147.0  600519\n",
       "2018-05-31  720.027  740.614  741.097  720.017  71852.0  600519\n",
       "2018-06-01  740.614  734.679  744.410  728.417  36177.0  600519\n",
       "2018-06-04  741.817  771.022  771.939  735.438  73805.0  600519\n",
       "2018-06-05  775.489  777.017  783.574  766.349  52629.0  600519\n",
       "2018-06-06  776.968  774.750  789.737  771.348  48969.0  600519\n",
       "2018-06-07  778.920  770.036  784.412  767.995  39167.0  600519\n",
       "2018-06-08  769.080  767.059  774.897  759.220  34958.0  600519\n",
       "2018-06-11  765.185  764.870  774.996  757.573  36547.0  600519\n",
       "2018-06-12  767.108  788.001  792.251  765.629  55287.0  600519\n",
       "2018-06-13  788.800  779.265  791.383  777.836  35244.0  600519\n",
       "2018-06-14  778.940  775.124  782.687  764.328  36159.0  600519\n",
       "2018-06-15  773.200  773.330  778.580  769.100  31707.0  600519\n",
       "2018-06-19  769.000  738.000  769.000  737.000  60195.0  600519\n",
       "2018-06-20  741.000  763.590  765.000  741.000  45838.0  600519\n",
       "2018-06-21  765.220  759.320  778.890  758.770  39182.0  600519\n",
       "2018-06-22  754.000  766.530  767.000  750.000  28854.0  600519\n",
       "2018-06-25  766.000  765.560  778.970  764.900  32934.0  600519\n",
       "2018-06-26  765.310  754.800  769.880  747.000  46577.0  600519\n",
       "2018-06-27  752.000  722.440  757.000  721.000  57298.0  600519\n",
       "2018-06-28  714.000  710.930  719.000  697.000  50833.0  600519\n",
       "2018-06-29  712.300  731.460  732.300  705.000  32929.0  600519\n",
       "2018-07-02  734.520  711.550  739.330  703.000  37558.0  600519\n",
       "2018-07-03  709.760  694.920  715.780  678.230  82837.0  600519\n",
       "2018-07-04  692.000  690.910  700.000  688.000  37990.0  600519\n",
       "2018-07-05  700.000  702.390  716.200  700.000  47123.0  600519\n",
       "2018-07-06  707.000  714.120  720.930  699.260  44156.0  600519\n",
       "2018-07-09  720.030  727.240  729.860  719.730  40572.0  600519\n",
       "2018-07-10  729.000  725.760  731.500  713.330  29010.0  600519\n",
       "2018-07-11  710.000  719.580  724.000  702.220  24278.0  600519\n",
       "2018-07-12  718.000  737.540  741.170  718.000  40170.0  600519\n",
       "2018-07-13  742.300  746.990  748.100  735.120  28907.0  600519\n",
       "2018-07-16  752.300  754.680  764.110  751.030  32474.0  600519\n",
       "2018-07-17  757.000  742.430  757.000  736.020  27806.0  600519\n",
       "2018-07-18  742.430  737.440  749.690  735.000  24521.0  600519\n",
       "2018-07-19  739.000  740.950  743.950  735.020  18078.0  600519\n",
       "2018-07-20  741.500  741.130  743.130  728.000  30548.0  600519\n",
       "2018-07-23  736.000  732.070  741.150  720.010  35969.0  600519\n",
       "2018-07-24  732.680  745.400  747.300  723.000  41808.0  600519\n",
       "2018-07-25  746.950  743.810  749.880  740.010  21743.0  600519\n",
       "2018-07-26  748.900  735.620  748.900  734.230  23067.0  600519\n",
       "2018-07-27  736.000  738.560  744.300  730.000  20913.0  600519"
      ]
     },
     "execution_count": 47,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.loc['2018',:]# 获得指定年份的切片数据"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 50,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "      <th>open</th>\n",
       "      <th>close</th>\n",
       "      <th>high</th>\n",
       "      <th>low</th>\n",
       "      <th>volume</th>\n",
       "      <th>code</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>date</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>2018-06-01</th>\n",
       "      <td>740.614</td>\n",
       "      <td>734.679</td>\n",
       "      <td>744.410</td>\n",
       "      <td>728.417</td>\n",
       "      <td>36177.0</td>\n",
       "      <td>600519</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2018-06-04</th>\n",
       "      <td>741.817</td>\n",
       "      <td>771.022</td>\n",
       "      <td>771.939</td>\n",
       "      <td>735.438</td>\n",
       "      <td>73805.0</td>\n",
       "      <td>600519</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2018-06-05</th>\n",
       "      <td>775.489</td>\n",
       "      <td>777.017</td>\n",
       "      <td>783.574</td>\n",
       "      <td>766.349</td>\n",
       "      <td>52629.0</td>\n",
       "      <td>600519</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2018-06-06</th>\n",
       "      <td>776.968</td>\n",
       "      <td>774.750</td>\n",
       "      <td>789.737</td>\n",
       "      <td>771.348</td>\n",
       "      <td>48969.0</td>\n",
       "      <td>600519</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2018-06-07</th>\n",
       "      <td>778.920</td>\n",
       "      <td>770.036</td>\n",
       "      <td>784.412</td>\n",
       "      <td>767.995</td>\n",
       "      <td>39167.0</td>\n",
       "      <td>600519</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2018-06-08</th>\n",
       "      <td>769.080</td>\n",
       "      <td>767.059</td>\n",
       "      <td>774.897</td>\n",
       "      <td>759.220</td>\n",
       "      <td>34958.0</td>\n",
       "      <td>600519</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2018-06-11</th>\n",
       "      <td>765.185</td>\n",
       "      <td>764.870</td>\n",
       "      <td>774.996</td>\n",
       "      <td>757.573</td>\n",
       "      <td>36547.0</td>\n",
       "      <td>600519</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2018-06-12</th>\n",
       "      <td>767.108</td>\n",
       "      <td>788.001</td>\n",
       "      <td>792.251</td>\n",
       "      <td>765.629</td>\n",
       "      <td>55287.0</td>\n",
       "      <td>600519</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2018-06-13</th>\n",
       "      <td>788.800</td>\n",
       "      <td>779.265</td>\n",
       "      <td>791.383</td>\n",
       "      <td>777.836</td>\n",
       "      <td>35244.0</td>\n",
       "      <td>600519</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2018-06-14</th>\n",
       "      <td>778.940</td>\n",
       "      <td>775.124</td>\n",
       "      <td>782.687</td>\n",
       "      <td>764.328</td>\n",
       "      <td>36159.0</td>\n",
       "      <td>600519</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2018-06-15</th>\n",
       "      <td>773.200</td>\n",
       "      <td>773.330</td>\n",
       "      <td>778.580</td>\n",
       "      <td>769.100</td>\n",
       "      <td>31707.0</td>\n",
       "      <td>600519</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "               open    close     high      low   volume    code\n",
       "date                                                           \n",
       "2018-06-01  740.614  734.679  744.410  728.417  36177.0  600519\n",
       "2018-06-04  741.817  771.022  771.939  735.438  73805.0  600519\n",
       "2018-06-05  775.489  777.017  783.574  766.349  52629.0  600519\n",
       "2018-06-06  776.968  774.750  789.737  771.348  48969.0  600519\n",
       "2018-06-07  778.920  770.036  784.412  767.995  39167.0  600519\n",
       "2018-06-08  769.080  767.059  774.897  759.220  34958.0  600519\n",
       "2018-06-11  765.185  764.870  774.996  757.573  36547.0  600519\n",
       "2018-06-12  767.108  788.001  792.251  765.629  55287.0  600519\n",
       "2018-06-13  788.800  779.265  791.383  777.836  35244.0  600519\n",
       "2018-06-14  778.940  775.124  782.687  764.328  36159.0  600519\n",
       "2018-06-15  773.200  773.330  778.580  769.100  31707.0  600519"
      ]
     },
     "execution_count": 50,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.loc['2018-06-01':'2018-06-15',:]#获得指定时间段的切片，且包含收尾数据行"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 53,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
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       "\n",
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       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>open</th>\n",
       "      <th>close</th>\n",
       "      <th>high</th>\n",
       "      <th>low</th>\n",
       "      <th>volume</th>\n",
       "      <th>code</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>date</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>2018-07-02</th>\n",
       "      <td>734.52</td>\n",
       "      <td>711.55</td>\n",
       "      <td>739.33</td>\n",
       "      <td>703.00</td>\n",
       "      <td>37558.0</td>\n",
       "      <td>600519</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2018-07-03</th>\n",
       "      <td>709.76</td>\n",
       "      <td>694.92</td>\n",
       "      <td>715.78</td>\n",
       "      <td>678.23</td>\n",
       "      <td>82837.0</td>\n",
       "      <td>600519</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2018-07-04</th>\n",
       "      <td>692.00</td>\n",
       "      <td>690.91</td>\n",
       "      <td>700.00</td>\n",
       "      <td>688.00</td>\n",
       "      <td>37990.0</td>\n",
       "      <td>600519</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2018-07-05</th>\n",
       "      <td>700.00</td>\n",
       "      <td>702.39</td>\n",
       "      <td>716.20</td>\n",
       "      <td>700.00</td>\n",
       "      <td>47123.0</td>\n",
       "      <td>600519</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2018-07-06</th>\n",
       "      <td>707.00</td>\n",
       "      <td>714.12</td>\n",
       "      <td>720.93</td>\n",
       "      <td>699.26</td>\n",
       "      <td>44156.0</td>\n",
       "      <td>600519</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2018-07-09</th>\n",
       "      <td>720.03</td>\n",
       "      <td>727.24</td>\n",
       "      <td>729.86</td>\n",
       "      <td>719.73</td>\n",
       "      <td>40572.0</td>\n",
       "      <td>600519</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2018-07-10</th>\n",
       "      <td>729.00</td>\n",
       "      <td>725.76</td>\n",
       "      <td>731.50</td>\n",
       "      <td>713.33</td>\n",
       "      <td>29010.0</td>\n",
       "      <td>600519</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2018-07-11</th>\n",
       "      <td>710.00</td>\n",
       "      <td>719.58</td>\n",
       "      <td>724.00</td>\n",
       "      <td>702.22</td>\n",
       "      <td>24278.0</td>\n",
       "      <td>600519</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2018-07-12</th>\n",
       "      <td>718.00</td>\n",
       "      <td>737.54</td>\n",
       "      <td>741.17</td>\n",
       "      <td>718.00</td>\n",
       "      <td>40170.0</td>\n",
       "      <td>600519</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2018-07-13</th>\n",
       "      <td>742.30</td>\n",
       "      <td>746.99</td>\n",
       "      <td>748.10</td>\n",
       "      <td>735.12</td>\n",
       "      <td>28907.0</td>\n",
       "      <td>600519</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2018-07-16</th>\n",
       "      <td>752.30</td>\n",
       "      <td>754.68</td>\n",
       "      <td>764.11</td>\n",
       "      <td>751.03</td>\n",
       "      <td>32474.0</td>\n",
       "      <td>600519</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2018-07-17</th>\n",
       "      <td>757.00</td>\n",
       "      <td>742.43</td>\n",
       "      <td>757.00</td>\n",
       "      <td>736.02</td>\n",
       "      <td>27806.0</td>\n",
       "      <td>600519</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2018-07-18</th>\n",
       "      <td>742.43</td>\n",
       "      <td>737.44</td>\n",
       "      <td>749.69</td>\n",
       "      <td>735.00</td>\n",
       "      <td>24521.0</td>\n",
       "      <td>600519</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2018-07-19</th>\n",
       "      <td>739.00</td>\n",
       "      <td>740.95</td>\n",
       "      <td>743.95</td>\n",
       "      <td>735.02</td>\n",
       "      <td>18078.0</td>\n",
       "      <td>600519</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2018-07-20</th>\n",
       "      <td>741.50</td>\n",
       "      <td>741.13</td>\n",
       "      <td>743.13</td>\n",
       "      <td>728.00</td>\n",
       "      <td>30548.0</td>\n",
       "      <td>600519</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2018-07-23</th>\n",
       "      <td>736.00</td>\n",
       "      <td>732.07</td>\n",
       "      <td>741.15</td>\n",
       "      <td>720.01</td>\n",
       "      <td>35969.0</td>\n",
       "      <td>600519</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2018-07-24</th>\n",
       "      <td>732.68</td>\n",
       "      <td>745.40</td>\n",
       "      <td>747.30</td>\n",
       "      <td>723.00</td>\n",
       "      <td>41808.0</td>\n",
       "      <td>600519</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2018-07-25</th>\n",
       "      <td>746.95</td>\n",
       "      <td>743.81</td>\n",
       "      <td>749.88</td>\n",
       "      <td>740.01</td>\n",
       "      <td>21743.0</td>\n",
       "      <td>600519</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2018-07-26</th>\n",
       "      <td>748.90</td>\n",
       "      <td>735.62</td>\n",
       "      <td>748.90</td>\n",
       "      <td>734.23</td>\n",
       "      <td>23067.0</td>\n",
       "      <td>600519</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2018-07-27</th>\n",
       "      <td>736.00</td>\n",
       "      <td>738.56</td>\n",
       "      <td>744.30</td>\n",
       "      <td>730.00</td>\n",
       "      <td>20913.0</td>\n",
       "      <td>600519</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "              open   close    high     low   volume    code\n",
       "date                                                       \n",
       "2018-07-02  734.52  711.55  739.33  703.00  37558.0  600519\n",
       "2018-07-03  709.76  694.92  715.78  678.23  82837.0  600519\n",
       "2018-07-04  692.00  690.91  700.00  688.00  37990.0  600519\n",
       "2018-07-05  700.00  702.39  716.20  700.00  47123.0  600519\n",
       "2018-07-06  707.00  714.12  720.93  699.26  44156.0  600519\n",
       "2018-07-09  720.03  727.24  729.86  719.73  40572.0  600519\n",
       "2018-07-10  729.00  725.76  731.50  713.33  29010.0  600519\n",
       "2018-07-11  710.00  719.58  724.00  702.22  24278.0  600519\n",
       "2018-07-12  718.00  737.54  741.17  718.00  40170.0  600519\n",
       "2018-07-13  742.30  746.99  748.10  735.12  28907.0  600519\n",
       "2018-07-16  752.30  754.68  764.11  751.03  32474.0  600519\n",
       "2018-07-17  757.00  742.43  757.00  736.02  27806.0  600519\n",
       "2018-07-18  742.43  737.44  749.69  735.00  24521.0  600519\n",
       "2018-07-19  739.00  740.95  743.95  735.02  18078.0  600519\n",
       "2018-07-20  741.50  741.13  743.13  728.00  30548.0  600519\n",
       "2018-07-23  736.00  732.07  741.15  720.01  35969.0  600519\n",
       "2018-07-24  732.68  745.40  747.30  723.00  41808.0  600519\n",
       "2018-07-25  746.95  743.81  749.88  740.01  21743.0  600519\n",
       "2018-07-26  748.90  735.62  748.90  734.23  23067.0  600519\n",
       "2018-07-27  736.00  738.56  744.30  730.00  20913.0  600519"
      ]
     },
     "execution_count": 53,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.loc['2018-06-30':,:]# 获得指定首尾到相关界限的数据"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 54,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>open</th>\n",
       "      <th>close</th>\n",
       "      <th>high</th>\n",
       "      <th>low</th>\n",
       "      <th>volume</th>\n",
       "      <th>code</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>date</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>2018-05-07</th>\n",
       "      <td>650.711</td>\n",
       "      <td>688.396</td>\n",
       "      <td>692.054</td>\n",
       "      <td>648.561</td>\n",
       "      <td>85591.0</td>\n",
       "      <td>600519</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2018-05-09</th>\n",
       "      <td>699.153</td>\n",
       "      <td>692.123</td>\n",
       "      <td>702.328</td>\n",
       "      <td>687.360</td>\n",
       "      <td>32331.0</td>\n",
       "      <td>600519</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2018-05-11</th>\n",
       "      <td>708.628</td>\n",
       "      <td>707.968</td>\n",
       "      <td>720.273</td>\n",
       "      <td>705.680</td>\n",
       "      <td>39141.0</td>\n",
       "      <td>600519</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "               open    close     high      low   volume    code\n",
       "date                                                           \n",
       "2018-05-07  650.711  688.396  692.054  648.561  85591.0  600519\n",
       "2018-05-09  699.153  692.123  702.328  687.360  32331.0  600519\n",
       "2018-05-11  708.628  707.968  720.273  705.680  39141.0  600519"
      ]
     },
     "execution_count": 54,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.loc[df.index[[0,2,4]],:]"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# 检查重复索引的时间序列"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 55,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "True"
      ]
     },
     "execution_count": 55,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.index.is_unique"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# 生成日期范围\n",
    "pandas.date_range可用于根据指定的频率生成指定长度的DatetimeIndex"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 56,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "DatetimeIndex(['2018-08-08', '2018-08-09', '2018-08-10', '2018-08-11',\n",
       "               '2018-08-12', '2018-08-13', '2018-08-14', '2018-08-15',\n",
       "               '2018-08-16', '2018-08-17', '2018-08-18'],\n",
       "              dtype='datetime64[ns]', freq='D')"
      ]
     },
     "execution_count": 56,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "index=pd.date_range('20180808','2018/8/18')\n",
    "index"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 57,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "DatetimeIndex(['2018-08-08', '2018-08-09', '2018-08-10', '2018-08-11',\n",
       "               '2018-08-12'],\n",
       "              dtype='datetime64[ns]', freq='D')"
      ]
     },
     "execution_count": 57,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "pd.date_range(start='20180808',periods=5)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "生成一个由每月最后一个工作日组成的日期索引，可以传入\"BM\"频率,样就只会包含时间间隔内（或刚好在边界上的）符合频率要求的日期："
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 60,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "DatetimeIndex(['2017-08-31', '2017-09-29', '2017-10-31', '2017-11-30',\n",
       "               '2017-12-29', '2018-01-31', '2018-02-28', '2018-03-30',\n",
       "               '2018-04-30', '2018-05-31'],\n",
       "              dtype='datetime64[ns]', freq='BM')"
      ]
     },
     "execution_count": 60,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "pd.date_range(start='20170831',end='2018-05-31',freq='BM')"
   ]
  },
  {
   "attachments": {
    "image.png": {
     "image/png": 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"
    }
   },
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "基本的时间序列频率:\n",
    "![image.png](attachment:image.png)"
   ]
  },
  {
   "attachments": {
    "image.png": {
     "image/png": 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"
    }
   },
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "![image.png](attachment:image.png)"
   ]
  },
  {
   "attachments": {
    "image.png": {
     "image/png": 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"
    }
   },
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "![image.png](attachment:image.png)\n",
    "有时，虽然起始和结束日期带有时间信息，但你希望产生一组被规范化（normalize）到午夜的时间戳。normalize选项即可实现该功能："
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 62,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "DatetimeIndex(['2012-05-02', '2012-05-03', '2012-05-04', '2012-05-05',\n",
       "               '2012-05-06'],\n",
       "              dtype='datetime64[ns]', freq='D')"
      ]
     },
     "execution_count": 62,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "pd.date_range('2012-05-02 12:56:31', periods=5, normalize=True)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# 频率和日期偏移量\n",
    "pandas中的频率是由一个基础频率（base frequency）和一个乘数组成的。基础频率通常以一个字符串别名表示，比如\"M\"表示每月，\"H\"表示每小时。对于每个基础频率，都有一个被称为日期偏移量（date offset）的对象与之对应。例如，按小时计算的频率可以用Hour类表示："
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 63,
   "metadata": {},
   "outputs": [],
   "source": [
    "from pandas.tseries.offsets import Hour,Minute"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 64,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<Hour>"
      ]
     },
     "execution_count": 64,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "Hour()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 65,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<5 * Hours>"
      ]
     },
     "execution_count": 65,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "Hour(5)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "一般来说，无需明确创建这样的对象，只需使用诸如\"H\"或\"4H\"这样的字符串别名即可。在基础频率前面放上一个整数即可创建倍数："
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 66,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "DatetimeIndex(['2018-08-01 00:00:00', '2018-08-01 04:00:00',\n",
       "               '2018-08-01 08:00:00', '2018-08-01 12:00:00',\n",
       "               '2018-08-01 16:00:00'],\n",
       "              dtype='datetime64[ns]', freq='4H')"
      ]
     },
     "execution_count": 66,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "pd.date_range('2018-08',periods=5,freq='4H')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "大部分偏移量对象都可通过加法进行连接"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 67,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<200 * Minutes>"
      ]
     },
     "execution_count": 67,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "Hour(3)+Minute(20)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "同理，你也可以传入频率字符串（如\"2h30min\"），这种字符串可以被高效地解析为等效的表达式："
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 69,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "DatetimeIndex(['2018-08-01 00:00:00', '2018-08-01 04:05:00',\n",
       "               '2018-08-01 08:10:00', '2018-08-01 12:15:00',\n",
       "               '2018-08-01 16:20:00'],\n",
       "              dtype='datetime64[ns]', freq='245T')"
      ]
     },
     "execution_count": 69,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "pd.date_range('2018-08',periods=5,freq='4H5min')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# WOM日期\n",
    "WOM（Week Of Month）是一种非常实用的频率类，它以WOM开头。它使你能获得诸如“每月第3个星期五”之类的日期："
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 70,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "DatetimeIndex(['2012-01-20', '2012-02-17', '2012-03-16', '2012-04-20',\n",
       "               '2012-05-18', '2012-06-15', '2012-07-20', '2012-08-17'],\n",
       "              dtype='datetime64[ns]', freq='WOM-3FRI')"
      ]
     },
     "execution_count": 70,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "pd.date_range('2012-01-01', '2012-09-01', freq='WOM-3FRI')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# 移动（超前和滞后）数据\n",
    "移动（shifting）指的是沿着时间轴将数据前移或后移。Series和DataFrame都有一个shift方法用于执行单纯的前移或后移操作，保持索引不变："
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 71,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>open</th>\n",
       "      <th>close</th>\n",
       "      <th>high</th>\n",
       "      <th>low</th>\n",
       "      <th>volume</th>\n",
       "      <th>code</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>date</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>2018-05-07</th>\n",
       "      <td>650.711</td>\n",
       "      <td>688.396</td>\n",
       "      <td>692.054</td>\n",
       "      <td>648.561</td>\n",
       "      <td>85591.0</td>\n",
       "      <td>600519</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2018-05-08</th>\n",
       "      <td>688.258</td>\n",
       "      <td>698.906</td>\n",
       "      <td>702.160</td>\n",
       "      <td>688.258</td>\n",
       "      <td>62497.0</td>\n",
       "      <td>600519</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2018-05-09</th>\n",
       "      <td>699.153</td>\n",
       "      <td>692.123</td>\n",
       "      <td>702.328</td>\n",
       "      <td>687.360</td>\n",
       "      <td>32331.0</td>\n",
       "      <td>600519</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2018-05-10</th>\n",
       "      <td>693.651</td>\n",
       "      <td>704.191</td>\n",
       "      <td>705.976</td>\n",
       "      <td>693.651</td>\n",
       "      <td>39293.0</td>\n",
       "      <td>600519</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2018-05-11</th>\n",
       "      <td>708.628</td>\n",
       "      <td>707.968</td>\n",
       "      <td>720.273</td>\n",
       "      <td>705.680</td>\n",
       "      <td>39141.0</td>\n",
       "      <td>600519</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "               open    close     high      low   volume    code\n",
       "date                                                           \n",
       "2018-05-07  650.711  688.396  692.054  648.561  85591.0  600519\n",
       "2018-05-08  688.258  698.906  702.160  688.258  62497.0  600519\n",
       "2018-05-09  699.153  692.123  702.328  687.360  32331.0  600519\n",
       "2018-05-10  693.651  704.191  705.976  693.651  39293.0  600519\n",
       "2018-05-11  708.628  707.968  720.273  705.680  39141.0  600519"
      ]
     },
     "execution_count": 71,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 72,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>open</th>\n",
       "      <th>close</th>\n",
       "      <th>high</th>\n",
       "      <th>low</th>\n",
       "      <th>volume</th>\n",
       "      <th>code</th>\n",
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       "    <tr>\n",
       "      <th>date</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>2018-05-07</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2018-05-08</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2018-05-09</th>\n",
       "      <td>650.711</td>\n",
       "      <td>688.396</td>\n",
       "      <td>692.054</td>\n",
       "      <td>648.561</td>\n",
       "      <td>85591.0</td>\n",
       "      <td>600519</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2018-05-10</th>\n",
       "      <td>688.258</td>\n",
       "      <td>698.906</td>\n",
       "      <td>702.160</td>\n",
       "      <td>688.258</td>\n",
       "      <td>62497.0</td>\n",
       "      <td>600519</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2018-05-11</th>\n",
       "      <td>699.153</td>\n",
       "      <td>692.123</td>\n",
       "      <td>702.328</td>\n",
       "      <td>687.360</td>\n",
       "      <td>32331.0</td>\n",
       "      <td>600519</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "               open    close     high      low   volume    code\n",
       "date                                                           \n",
       "2018-05-07      NaN      NaN      NaN      NaN      NaN     NaN\n",
       "2018-05-08      NaN      NaN      NaN      NaN      NaN     NaN\n",
       "2018-05-09  650.711  688.396  692.054  648.561  85591.0  600519\n",
       "2018-05-10  688.258  698.906  702.160  688.258  62497.0  600519\n",
       "2018-05-11  699.153  692.123  702.328  687.360  32331.0  600519"
      ]
     },
     "execution_count": 72,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.shift(2).head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 73,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
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       "\n",
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       "<table border=\"1\" class=\"dataframe\">\n",
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       "      <th>open</th>\n",
       "      <th>close</th>\n",
       "      <th>high</th>\n",
       "      <th>low</th>\n",
       "      <th>volume</th>\n",
       "      <th>code</th>\n",
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       "    <tr>\n",
       "      <th>date</th>\n",
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       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>2018-07-23</th>\n",
       "      <td>736.00</td>\n",
       "      <td>732.07</td>\n",
       "      <td>741.15</td>\n",
       "      <td>720.01</td>\n",
       "      <td>35969.0</td>\n",
       "      <td>600519</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2018-07-24</th>\n",
       "      <td>732.68</td>\n",
       "      <td>745.40</td>\n",
       "      <td>747.30</td>\n",
       "      <td>723.00</td>\n",
       "      <td>41808.0</td>\n",
       "      <td>600519</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2018-07-25</th>\n",
       "      <td>746.95</td>\n",
       "      <td>743.81</td>\n",
       "      <td>749.88</td>\n",
       "      <td>740.01</td>\n",
       "      <td>21743.0</td>\n",
       "      <td>600519</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2018-07-26</th>\n",
       "      <td>748.90</td>\n",
       "      <td>735.62</td>\n",
       "      <td>748.90</td>\n",
       "      <td>734.23</td>\n",
       "      <td>23067.0</td>\n",
       "      <td>600519</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2018-07-27</th>\n",
       "      <td>736.00</td>\n",
       "      <td>738.56</td>\n",
       "      <td>744.30</td>\n",
       "      <td>730.00</td>\n",
       "      <td>20913.0</td>\n",
       "      <td>600519</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "              open   close    high     low   volume    code\n",
       "date                                                       \n",
       "2018-07-23  736.00  732.07  741.15  720.01  35969.0  600519\n",
       "2018-07-24  732.68  745.40  747.30  723.00  41808.0  600519\n",
       "2018-07-25  746.95  743.81  749.88  740.01  21743.0  600519\n",
       "2018-07-26  748.90  735.62  748.90  734.23  23067.0  600519\n",
       "2018-07-27  736.00  738.56  744.30  730.00  20913.0  600519"
      ]
     },
     "execution_count": 73,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.tail()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 74,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
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       "    <tr>\n",
       "      <th>date</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>2018-07-23</th>\n",
       "      <td>746.95</td>\n",
       "      <td>743.81</td>\n",
       "      <td>749.88</td>\n",
       "      <td>740.01</td>\n",
       "      <td>21743.0</td>\n",
       "      <td>600519</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2018-07-24</th>\n",
       "      <td>748.90</td>\n",
       "      <td>735.62</td>\n",
       "      <td>748.90</td>\n",
       "      <td>734.23</td>\n",
       "      <td>23067.0</td>\n",
       "      <td>600519</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2018-07-25</th>\n",
       "      <td>736.00</td>\n",
       "      <td>738.56</td>\n",
       "      <td>744.30</td>\n",
       "      <td>730.00</td>\n",
       "      <td>20913.0</td>\n",
       "      <td>600519</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2018-07-26</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2018-07-27</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "              open   close    high     low   volume    code\n",
       "date                                                       \n",
       "2018-07-23  746.95  743.81  749.88  740.01  21743.0  600519\n",
       "2018-07-24  748.90  735.62  748.90  734.23  23067.0  600519\n",
       "2018-07-25  736.00  738.56  744.30  730.00  20913.0  600519\n",
       "2018-07-26     NaN     NaN     NaN     NaN      NaN     NaN\n",
       "2018-07-27     NaN     NaN     NaN     NaN      NaN     NaN"
      ]
     },
     "execution_count": 74,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.shift(-2).tail()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "当我们这样进行移动时，就会在时间序列的前面或后面产生缺失数据。\n",
    "\n",
    "shift通常用于计算一个时间序列或多个时间序列（如DataFrame的列）中的百分比变化。可以这样表达："
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 75,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
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       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>close</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>date</th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>2018-05-07</th>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2018-05-08</th>\n",
       "      <td>0.015267</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2018-05-09</th>\n",
       "      <td>-0.009705</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2018-05-10</th>\n",
       "      <td>0.017436</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2018-05-11</th>\n",
       "      <td>0.005364</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "               close\n",
       "date                \n",
       "2018-05-07       NaN\n",
       "2018-05-08  0.015267\n",
       "2018-05-09 -0.009705\n",
       "2018-05-10  0.017436\n",
       "2018-05-11  0.005364"
      ]
     },
     "execution_count": 75,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "(df.iloc[:,[1]]/df.iloc[:,[1]].shift(1)-1).head()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "由于单纯的移位操作不会修改索引，所以部分数据会被丢弃。因此，如果频率已知，则可以将其传给shift以便实现对时间戳进行位移而不是对数据进行简单位移："
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 76,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
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       "</style>\n",
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       "      <th>close</th>\n",
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       "    <tr>\n",
       "      <th>date</th>\n",
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       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
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       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>2018-05-08</th>\n",
       "      <td>650.711</td>\n",
       "      <td>688.396</td>\n",
       "      <td>692.054</td>\n",
       "      <td>648.561</td>\n",
       "      <td>85591.0</td>\n",
       "      <td>600519</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2018-05-09</th>\n",
       "      <td>688.258</td>\n",
       "      <td>698.906</td>\n",
       "      <td>702.160</td>\n",
       "      <td>688.258</td>\n",
       "      <td>62497.0</td>\n",
       "      <td>600519</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2018-05-10</th>\n",
       "      <td>699.153</td>\n",
       "      <td>692.123</td>\n",
       "      <td>702.328</td>\n",
       "      <td>687.360</td>\n",
       "      <td>32331.0</td>\n",
       "      <td>600519</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2018-05-11</th>\n",
       "      <td>693.651</td>\n",
       "      <td>704.191</td>\n",
       "      <td>705.976</td>\n",
       "      <td>693.651</td>\n",
       "      <td>39293.0</td>\n",
       "      <td>600519</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2018-05-12</th>\n",
       "      <td>708.628</td>\n",
       "      <td>707.968</td>\n",
       "      <td>720.273</td>\n",
       "      <td>705.680</td>\n",
       "      <td>39141.0</td>\n",
       "      <td>600519</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "               open    close     high      low   volume    code\n",
       "date                                                           \n",
       "2018-05-08  650.711  688.396  692.054  648.561  85591.0  600519\n",
       "2018-05-09  688.258  698.906  702.160  688.258  62497.0  600519\n",
       "2018-05-10  699.153  692.123  702.328  687.360  32331.0  600519\n",
       "2018-05-11  693.651  704.191  705.976  693.651  39293.0  600519\n",
       "2018-05-12  708.628  707.968  720.273  705.680  39141.0  600519"
      ]
     },
     "execution_count": 76,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.shift(1,freq='1D').head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 77,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
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       "      <th>close</th>\n",
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       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
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       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>2018-05-07</th>\n",
       "      <td>650.711</td>\n",
       "      <td>688.396</td>\n",
       "      <td>692.054</td>\n",
       "      <td>648.561</td>\n",
       "      <td>85591.0</td>\n",
       "      <td>600519</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2018-05-08</th>\n",
       "      <td>688.258</td>\n",
       "      <td>698.906</td>\n",
       "      <td>702.160</td>\n",
       "      <td>688.258</td>\n",
       "      <td>62497.0</td>\n",
       "      <td>600519</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2018-05-09</th>\n",
       "      <td>699.153</td>\n",
       "      <td>692.123</td>\n",
       "      <td>702.328</td>\n",
       "      <td>687.360</td>\n",
       "      <td>32331.0</td>\n",
       "      <td>600519</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2018-05-10</th>\n",
       "      <td>693.651</td>\n",
       "      <td>704.191</td>\n",
       "      <td>705.976</td>\n",
       "      <td>693.651</td>\n",
       "      <td>39293.0</td>\n",
       "      <td>600519</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2018-05-11</th>\n",
       "      <td>708.628</td>\n",
       "      <td>707.968</td>\n",
       "      <td>720.273</td>\n",
       "      <td>705.680</td>\n",
       "      <td>39141.0</td>\n",
       "      <td>600519</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "               open    close     high      low   volume    code\n",
       "date                                                           \n",
       "2018-05-07  650.711  688.396  692.054  648.561  85591.0  600519\n",
       "2018-05-08  688.258  698.906  702.160  688.258  62497.0  600519\n",
       "2018-05-09  699.153  692.123  702.328  687.360  32331.0  600519\n",
       "2018-05-10  693.651  704.191  705.976  693.651  39293.0  600519\n",
       "2018-05-11  708.628  707.968  720.273  705.680  39141.0  600519"
      ]
     },
     "execution_count": 77,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.head()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# 重采样及频率转换 \n",
    "重采样（resampling）指的是将时间序列从一个频率转换到另一个频率的处理过程。将高频率数据聚合到低频率称为降采样（downsampling），而将低频率数据转换到高频率则称为升采样（upsampling）。<br>\n",
    "pandas对象都带有一个resample方法，它是各种频率转换工作的主力函数。resample有一个类似于groupby的API，调用resample可以分组数据，然后会调用一个聚合函数："
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 78,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>open</th>\n",
       "      <th>close</th>\n",
       "      <th>high</th>\n",
       "      <th>low</th>\n",
       "      <th>volume</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>date</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>2018-05-13</th>\n",
       "      <td>688.0802</td>\n",
       "      <td>698.3168</td>\n",
       "      <td>704.5582</td>\n",
       "      <td>684.7020</td>\n",
       "      <td>51770.6</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2018-05-20</th>\n",
       "      <td>723.5484</td>\n",
       "      <td>727.0154</td>\n",
       "      <td>732.3220</td>\n",
       "      <td>717.1118</td>\n",
       "      <td>35527.2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2018-05-27</th>\n",
       "      <td>720.0206</td>\n",
       "      <td>715.9208</td>\n",
       "      <td>726.2482</td>\n",
       "      <td>712.1050</td>\n",
       "      <td>26250.4</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2018-06-03</th>\n",
       "      <td>722.8170</td>\n",
       "      <td>728.4450</td>\n",
       "      <td>736.4552</td>\n",
       "      <td>716.9106</td>\n",
       "      <td>45760.2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2018-06-10</th>\n",
       "      <td>768.4548</td>\n",
       "      <td>771.9768</td>\n",
       "      <td>780.9118</td>\n",
       "      <td>760.0700</td>\n",
       "      <td>49905.6</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                open     close      high       low   volume\n",
       "date                                                       \n",
       "2018-05-13  688.0802  698.3168  704.5582  684.7020  51770.6\n",
       "2018-05-20  723.5484  727.0154  732.3220  717.1118  35527.2\n",
       "2018-05-27  720.0206  715.9208  726.2482  712.1050  26250.4\n",
       "2018-06-03  722.8170  728.4450  736.4552  716.9106  45760.2\n",
       "2018-06-10  768.4548  771.9768  780.9118  760.0700  49905.6"
      ]
     },
     "execution_count": 78,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.resample('1W').mean().head()"
   ]
  },
  {
   "attachments": {
    "image.png": {
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"
    }
   },
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    " resample方法的参数:\n",
    " ![image.png](attachment:image.png)\n",
    " # 降采样\n",
    "将数据聚合到规律的低频率是一件非常普通的时间序列处理任务。待聚合的数据不必拥有固定的频率，期望的频率会自动定义聚合的面元边界，这些面元用于将时间序列拆分为多个片段。例如，要转换到月度频率（'M'或'BM'），数据需要被划分到多个单月时间段中。各时间段都是半开放的。一个数据点只能属于一个时间段，所有时间段的并集必须能组成整个时间帧。在用resample对数据进行降采样时，需要考虑两样东西：\n",
    "* 各区间哪边是闭合的。\n",
    "* 如何标记各个聚合面元，用区间的开头还是末尾。"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 81,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>open</th>\n",
       "      <th>close</th>\n",
       "      <th>high</th>\n",
       "      <th>low</th>\n",
       "      <th>volume</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>date</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>2018-05-13</th>\n",
       "      <td>3440.401</td>\n",
       "      <td>3491.584</td>\n",
       "      <td>3522.791</td>\n",
       "      <td>3423.510</td>\n",
       "      <td>258853.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2018-05-27</th>\n",
       "      <td>7217.845</td>\n",
       "      <td>7214.681</td>\n",
       "      <td>7292.851</td>\n",
       "      <td>7146.084</td>\n",
       "      <td>308888.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2018-06-10</th>\n",
       "      <td>7456.359</td>\n",
       "      <td>7502.109</td>\n",
       "      <td>7586.835</td>\n",
       "      <td>7384.903</td>\n",
       "      <td>478329.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2018-06-24</th>\n",
       "      <td>6902.453</td>\n",
       "      <td>6908.030</td>\n",
       "      <td>6999.787</td>\n",
       "      <td>6821.236</td>\n",
       "      <td>369013.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2018-07-08</th>\n",
       "      <td>7252.890</td>\n",
       "      <td>7199.080</td>\n",
       "      <td>7349.390</td>\n",
       "      <td>7103.390</td>\n",
       "      <td>470235.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2018-07-22</th>\n",
       "      <td>7351.560</td>\n",
       "      <td>7373.740</td>\n",
       "      <td>7432.510</td>\n",
       "      <td>7273.470</td>\n",
       "      <td>296364.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2018-08-05</th>\n",
       "      <td>3700.530</td>\n",
       "      <td>3695.460</td>\n",
       "      <td>3731.530</td>\n",
       "      <td>3647.250</td>\n",
       "      <td>143500.0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                open     close      high       low    volume\n",
       "date                                                        \n",
       "2018-05-13  3440.401  3491.584  3522.791  3423.510  258853.0\n",
       "2018-05-27  7217.845  7214.681  7292.851  7146.084  308888.0\n",
       "2018-06-10  7456.359  7502.109  7586.835  7384.903  478329.0\n",
       "2018-06-24  6902.453  6908.030  6999.787  6821.236  369013.0\n",
       "2018-07-08  7252.890  7199.080  7349.390  7103.390  470235.0\n",
       "2018-07-22  7351.560  7373.740  7432.510  7273.470  296364.0\n",
       "2018-08-05  3700.530  3695.460  3731.530  3647.250  143500.0"
      ]
     },
     "execution_count": 81,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.resample('2W',closed='right',label='right').sum()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# OHLC重采样\n",
    "金融领域中有一种无所不在的时间序列聚合方式，即计算各面元的四个值：第一个值（open，开盘）、最后一个值（close，收盘）、最大值（high，最高）以及最小值（low，最低）。传入how='ohlc'即可得到一个含有这四种聚合值的DataFrame。整个过程很高效，只需一次扫描即可计算出结果："
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 82,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
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       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
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       "\n",
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       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>open</th>\n",
       "      <th>high</th>\n",
       "      <th>low</th>\n",
       "      <th>close</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>date</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>2018-05-13</th>\n",
       "      <td>688.396</td>\n",
       "      <td>707.968</td>\n",
       "      <td>688.396</td>\n",
       "      <td>707.968</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2018-05-27</th>\n",
       "      <td>732.016</td>\n",
       "      <td>732.657</td>\n",
       "      <td>705.384</td>\n",
       "      <td>706.824</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2018-06-10</th>\n",
       "      <td>730.034</td>\n",
       "      <td>777.017</td>\n",
       "      <td>715.708</td>\n",
       "      <td>767.059</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2018-06-24</th>\n",
       "      <td>764.870</td>\n",
       "      <td>788.001</td>\n",
       "      <td>738.000</td>\n",
       "      <td>766.530</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2018-07-08</th>\n",
       "      <td>765.560</td>\n",
       "      <td>765.560</td>\n",
       "      <td>690.910</td>\n",
       "      <td>714.120</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2018-07-22</th>\n",
       "      <td>727.240</td>\n",
       "      <td>754.680</td>\n",
       "      <td>719.580</td>\n",
       "      <td>741.130</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2018-08-05</th>\n",
       "      <td>732.070</td>\n",
       "      <td>745.400</td>\n",
       "      <td>732.070</td>\n",
       "      <td>738.560</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "               open     high      low    close\n",
       "date                                          \n",
       "2018-05-13  688.396  707.968  688.396  707.968\n",
       "2018-05-27  732.016  732.657  705.384  706.824\n",
       "2018-06-10  730.034  777.017  715.708  767.059\n",
       "2018-06-24  764.870  788.001  738.000  766.530\n",
       "2018-07-08  765.560  765.560  690.910  714.120\n",
       "2018-07-22  727.240  754.680  719.580  741.130\n",
       "2018-08-05  732.070  745.400  732.070  738.560"
      ]
     },
     "execution_count": 82,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.close.resample('2W').ohlc()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# 升采样和插值"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 84,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
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       "<table border=\"1\" class=\"dataframe\">\n",
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       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>open</th>\n",
       "      <th>close</th>\n",
       "      <th>high</th>\n",
       "      <th>low</th>\n",
       "      <th>volume</th>\n",
       "      <th>code</th>\n",
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       "      <th>date</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>2018-05-07 00:00:00</th>\n",
       "      <td>650.711</td>\n",
       "      <td>688.396</td>\n",
       "      <td>692.054</td>\n",
       "      <td>648.561</td>\n",
       "      <td>85591.0</td>\n",
       "      <td>600519</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2018-05-07 12:00:00</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2018-05-08 00:00:00</th>\n",
       "      <td>688.258</td>\n",
       "      <td>698.906</td>\n",
       "      <td>702.160</td>\n",
       "      <td>688.258</td>\n",
       "      <td>62497.0</td>\n",
       "      <td>600519</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2018-05-08 12:00:00</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2018-05-09 00:00:00</th>\n",
       "      <td>699.153</td>\n",
       "      <td>692.123</td>\n",
       "      <td>702.328</td>\n",
       "      <td>687.360</td>\n",
       "      <td>32331.0</td>\n",
       "      <td>600519</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                        open    close     high      low   volume    code\n",
       "date                                                                    \n",
       "2018-05-07 00:00:00  650.711  688.396  692.054  648.561  85591.0  600519\n",
       "2018-05-07 12:00:00      NaN      NaN      NaN      NaN      NaN     NaN\n",
       "2018-05-08 00:00:00  688.258  698.906  702.160  688.258  62497.0  600519\n",
       "2018-05-08 12:00:00      NaN      NaN      NaN      NaN      NaN     NaN\n",
       "2018-05-09 00:00:00  699.153  692.123  702.328  687.360  32331.0  600519"
      ]
     },
     "execution_count": 84,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.resample('12H').asfreq().head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 85,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
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       "      <th></th>\n",
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       "  <tbody>\n",
       "    <tr>\n",
       "      <th>2018-05-07 00:00:00</th>\n",
       "      <td>650.711</td>\n",
       "      <td>688.396</td>\n",
       "      <td>692.054</td>\n",
       "      <td>648.561</td>\n",
       "      <td>85591.0</td>\n",
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       "    <tr>\n",
       "      <th>2018-05-07 12:00:00</th>\n",
       "      <td>650.711</td>\n",
       "      <td>688.396</td>\n",
       "      <td>692.054</td>\n",
       "      <td>648.561</td>\n",
       "      <td>85591.0</td>\n",
       "      <td>600519</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2018-05-08 00:00:00</th>\n",
       "      <td>688.258</td>\n",
       "      <td>698.906</td>\n",
       "      <td>702.160</td>\n",
       "      <td>688.258</td>\n",
       "      <td>62497.0</td>\n",
       "      <td>600519</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2018-05-08 12:00:00</th>\n",
       "      <td>688.258</td>\n",
       "      <td>698.906</td>\n",
       "      <td>702.160</td>\n",
       "      <td>688.258</td>\n",
       "      <td>62497.0</td>\n",
       "      <td>600519</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2018-05-09 00:00:00</th>\n",
       "      <td>699.153</td>\n",
       "      <td>692.123</td>\n",
       "      <td>702.328</td>\n",
       "      <td>687.360</td>\n",
       "      <td>32331.0</td>\n",
       "      <td>600519</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                        open    close     high      low   volume    code\n",
       "date                                                                    \n",
       "2018-05-07 00:00:00  650.711  688.396  692.054  648.561  85591.0  600519\n",
       "2018-05-07 12:00:00  650.711  688.396  692.054  648.561  85591.0  600519\n",
       "2018-05-08 00:00:00  688.258  698.906  702.160  688.258  62497.0  600519\n",
       "2018-05-08 12:00:00  688.258  698.906  702.160  688.258  62497.0  600519\n",
       "2018-05-09 00:00:00  699.153  692.123  702.328  687.360  32331.0  600519"
      ]
     },
     "execution_count": 85,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.resample('12H').ffill().head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 86,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
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       "<table border=\"1\" class=\"dataframe\">\n",
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       "      <th>close</th>\n",
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       "      <th>code</th>\n",
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       "      <th>date</th>\n",
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       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>2018-05-07 00:00:00</th>\n",
       "      <td>650.711</td>\n",
       "      <td>688.396</td>\n",
       "      <td>692.054</td>\n",
       "      <td>648.561</td>\n",
       "      <td>85591.0</td>\n",
       "      <td>600519</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2018-05-07 12:00:00</th>\n",
       "      <td>650.711</td>\n",
       "      <td>688.396</td>\n",
       "      <td>692.054</td>\n",
       "      <td>648.561</td>\n",
       "      <td>85591.0</td>\n",
       "      <td>600519</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2018-05-08 00:00:00</th>\n",
       "      <td>688.258</td>\n",
       "      <td>698.906</td>\n",
       "      <td>702.160</td>\n",
       "      <td>688.258</td>\n",
       "      <td>62497.0</td>\n",
       "      <td>600519</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2018-05-08 12:00:00</th>\n",
       "      <td>688.258</td>\n",
       "      <td>698.906</td>\n",
       "      <td>702.160</td>\n",
       "      <td>688.258</td>\n",
       "      <td>62497.0</td>\n",
       "      <td>600519</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2018-05-09 00:00:00</th>\n",
       "      <td>699.153</td>\n",
       "      <td>692.123</td>\n",
       "      <td>702.328</td>\n",
       "      <td>687.360</td>\n",
       "      <td>32331.0</td>\n",
       "      <td>600519</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2018-05-09 12:00:00</th>\n",
       "      <td>699.153</td>\n",
       "      <td>692.123</td>\n",
       "      <td>702.328</td>\n",
       "      <td>687.360</td>\n",
       "      <td>32331.0</td>\n",
       "      <td>600519</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2018-05-10 00:00:00</th>\n",
       "      <td>693.651</td>\n",
       "      <td>704.191</td>\n",
       "      <td>705.976</td>\n",
       "      <td>693.651</td>\n",
       "      <td>39293.0</td>\n",
       "      <td>600519</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2018-05-10 12:00:00</th>\n",
       "      <td>693.651</td>\n",
       "      <td>704.191</td>\n",
       "      <td>705.976</td>\n",
       "      <td>693.651</td>\n",
       "      <td>39293.0</td>\n",
       "      <td>600519</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2018-05-11 00:00:00</th>\n",
       "      <td>708.628</td>\n",
       "      <td>707.968</td>\n",
       "      <td>720.273</td>\n",
       "      <td>705.680</td>\n",
       "      <td>39141.0</td>\n",
       "      <td>600519</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2018-05-11 12:00:00</th>\n",
       "      <td>708.628</td>\n",
       "      <td>707.968</td>\n",
       "      <td>720.273</td>\n",
       "      <td>705.680</td>\n",
       "      <td>39141.0</td>\n",
       "      <td>600519</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2018-05-12 00:00:00</th>\n",
       "      <td>708.628</td>\n",
       "      <td>707.968</td>\n",
       "      <td>720.273</td>\n",
       "      <td>705.680</td>\n",
       "      <td>39141.0</td>\n",
       "      <td>600519</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                        open    close     high      low   volume    code\n",
       "date                                                                    \n",
       "2018-05-07 00:00:00  650.711  688.396  692.054  648.561  85591.0  600519\n",
       "2018-05-07 12:00:00  650.711  688.396  692.054  648.561  85591.0  600519\n",
       "2018-05-08 00:00:00  688.258  698.906  702.160  688.258  62497.0  600519\n",
       "2018-05-08 12:00:00  688.258  698.906  702.160  688.258  62497.0  600519\n",
       "2018-05-09 00:00:00  699.153  692.123  702.328  687.360  32331.0  600519\n",
       "2018-05-09 12:00:00  699.153  692.123  702.328  687.360  32331.0  600519\n",
       "2018-05-10 00:00:00  693.651  704.191  705.976  693.651  39293.0  600519\n",
       "2018-05-10 12:00:00  693.651  704.191  705.976  693.651  39293.0  600519\n",
       "2018-05-11 00:00:00  708.628  707.968  720.273  705.680  39141.0  600519\n",
       "2018-05-11 12:00:00  708.628  707.968  720.273  705.680  39141.0  600519\n",
       "2018-05-12 00:00:00  708.628  707.968  720.273  705.680  39141.0  600519"
      ]
     },
     "execution_count": 86,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.resample('12H').ffill(limit=2).head(11)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# 移动窗口函数\n",
    "在移动窗口（可以带有指数衰减权数）上计算的各种统计函数也是一类常见于时间序列的数组变换。这样可以圆滑噪音数据或断裂数据。我将它们称为移动窗口函数（moving window function），其中还包括那些窗口不定长的函数（如指数加权移动平均）。跟其他统计函数一样，移动窗口函数也会自动排除缺失值。<br>\n",
    "它与resample和groupby很像。"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 89,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.legend.Legend at 0x22e2fe144e0>"
      ]
     },
     "execution_count": 89,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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GLV2OMSNOi9PvyCpj2NRhds+7HQYDzLkXUm6HknQoTkMWHaGl7DhutCBMzWBqgpZG7dVYrXn8pibLqxnqy2D76xA/H876PcTNA52bUigGP8rQK1xGakE1BoHDzT2uTRkBwMc7c3nm21Se+TaVM0YGs3RyDBdOiu7guXcrf7D/v1BTCMs+6La4aVx0AP6ebmzPLuNSZw29FXdviJ4M0ZN5e2MWf9p9mEBvdxLDfUkI9yMh1peEMD9GRfgyIsQXD7c2EdXGatj5tvZk8O7FkLBQe1JQ+foKO1B3i8JlpBdUExfqi5e7Y1WjQgiuO3Mk1505kpzSOr7cn8+qvfn8cdUhnvjyEHNGhXHx5BgWT4gi0Nu9e/mDw19A+NgeQyBGg2DayGDHF2R74OsDJxkR4sO80WFkFtewPr2YT3ad6i5kNAiGB3uTGO5HQrgvSVEBXDLzHtxT7oANf4X1z8LxTZAw3yXzUwxOlKFXuIy0wmqb8udtYUSoD3cvHMXdC0eRVlDNl/vyWbUvnwc/2c//rjzIgqRwMotrOg/b1BRpxvGsB2y6Vkp8CM99l0Z5bRPBvvq1OSyvbWJPTjn3nD2a3547pnV7dUMzWSW1ZBbXcKy4lmPF2vuNGSU0tpjx8zRy/sRomHsfbH5JK/ZShl5hB8rQK1xCQ7OJ7NJalk7Wt/clQFKUP0lRSfzuvDHsy61k1d58vtqfT1F1IxdOiup4wpFVIM0w/lKbxrfG6XceL+fc8ZG6zXv90WLMEs4e234h2N/LneTYIJJj20s4NzSbmPjH79ifW6kZeg9fGLVIW9i94FltDUChsAFl6BUuIaOoBimxO7XSHoQQTBkexJThQTxy0Tj25JQTG+zT8cDDX0DoaIgYZ9O4ybGBeBgN7Mgu09XQr00tItTXg+RhgTYd7+VuZEykPwctMhIAjFuqGfq8XTB8hm5zUwxulEugcAmpBVrGjb2plY5iNAimx4UQFXiaoFlNMWRv1BqK2Jit4uVuZPLwQLY7EKeXUnLnf3bxw+H2ej0ms+Tn9GLmJ4XblCpqZeKwAA7lVZ6S5h2zWEvRPLLK7rkphi7K0CtcQnphNR5uBuJCO/Gwe5PUL+0K21iZERfCwbxK6prs09ypaWzh24MF/OmrQ+2aju89UU5FXTMLkzrP3++KicMCKa1toqDKUjjmHaSlWh75UlXcKmxGGXqFS0gtqGZUuJ/DcsO6cehzCEmEyAl2nTYjPoQWs2RvToVd55XVarn8J8rq+XxPXuv2talFGA2Cs0aH2zXehBgtzHMwr034ZvxSKM9SWjoKm1GGXuES0guqHSqU0pXaErvDNlbOGBmMEPYLnJVaDL2Hm4FX1mXQYvHq16UWc8aIYJvE3doyLtofg4CDeZWnNiZdBAjNq1cobKBHQy+ESBJC7G3zqhJC3GfZ9z9CiDQhxCEhxLNtznlICJFh2bfYlR9A0f+orGumoKqBMX1t6FO/AmmyO2wDEODlztioAHbYaejLajRDf/u8eLItuf8FlQ0cPlnFwrH2hW0AfDzcSAz341B+G0PvFw4jZytDr7CZHrNupJRpwBQAIYQRyANWCiEWApcAyVLKRiFEhOWY8cAyYAIQA6wRQoyRUppc9BkU/Qx7NOhdyqHPITgeoiY5dHpKXDArdubSbDLjbmMIyhq6WTZjBD8eKeKltRnUNWm3/ulplbYycVggWzJL228cdzGs/gOUZkJookPjKoYO9oZuFgGZUsrjwJ3AM1LKRgAppbVb8iXAR1LKRillFpABpOg1YUX/p9XQ96VHX1emCZiNv8RhbZgZ8SGnGobbiDV0E+rnwb2LRnOsuJa/fp9OTKAXYyIdk4KYEBNAQVUDxdWNpzaOXaL9q7x6hQ3Ya+iXAR9a3o8B5gkhtgkhfhZCWJN6hwEn2pyTa9nWDiHEHUKInUKInUOx2e9gJq2gCn8vN6JPT3XsTdK/s4Rtljo8REobgTNbKattxMvdgI+HG+dPiGJ0hB9ltU0sHBvRuTSDDUy05N23C98EDdcE2lSapcIGbDb0QggPYCnwsWWTGxAMzAQeAFYI7U7u7G7ukAcmpXxDSjldSjk9PNy+TARF/ya9oIakSH+HDZsupH4F/jEQPdXhISICvBhpaRhuK6W1TYT6ajIMBoPgN+eMBuAcJwqvxscEAHR8shh7kVY4VV3g8NiKoYE9Hv0FwG4ppbUSJBf4TGpsB8xAmGX78DbnxQL5ekxW0f+RUpJaUNW3C7FNdZDxo2YInZQJmGFrw3ALZbVNhLTRx1mSHMPq++axYIzjzkyAlzsjQ33aZ96AJfsGSPvW4bEVQwN7vgXXcCpsA/A5cDaAEGIM4AGUAKuAZUIITyFEPDAa2K7PdBX9ncKqRqoaWvo2tTJzLbTUw7glTg9lb8Pw0w09wNioAKefbibGBHb06CPGQXAcpH3j1NiKwY9Nhl4I4QOcC3zWZvO/gQQhxEHgI+Ami3d/CFgBHAZWA3erjJuhg3UhtrekDzol9SvwCoKRc3o+tgfsbRheWtNEqI6Kl1YmDAsgp6yOyro2rQiFgKQL4djP0GjbD5FiaGKToZdS1kkpQ6WUlW22NUkpr5dSTpRSTpNSrm2z7ykpZaKUMklKqZ4rhxBpBZrX2WeplaYWLZQx5nytJZ+T2NswvDOPXg8mWipkD508PXxzIZgatacYhaILVGWsQlfSCmqI8PfUVcfdLo5vgoYKLT6vA/Y0DK9vMlHfbCKkq+bkTjDBuiCbd1r4ZsQs7elFhW8U3aAMvUJX0gqr+jZ/PvVrcPPSdNt1YkZcCHkV9eRV1Hd7XGmtlufuitBNqJ8nMYFeHMw/zaM3ummKlumrtacZhaITlKFX6IbJLDlaWNN3YRspNUOfuEhr0qETrY1IeojTW6tiQ3w76XKlAxOGBXbMvAEtfFNfDie2uuS6ioGPMvQK3TheWktji7nvUitP7oWqXN3CNlZaG4b3EKcvbTX0rglbjY8O4FhJLQ3Np+U2jFoERg+VZtmGDUeLWfz39RRVN/T1VPoFytArdCPdknHTZ6mVR74CYYCkC3QdtrVheE8evUXQzBWhG4CIAE+khIq2mTcAnv4Qf5b2NKM06jlWXMPd7+8mrbCaXTasrQwFlKFX6EZaQQ1CwKgIxzRdHKapDn5+Dra+CnFzwSdE90ukxIeQXlhDucVr74zW0I0LFmMBAr21LKLK+uaOO5Mu1DTqi1Ndcu2BQlVDM7ct34mb0YAQp9J9hzrK0Ct0I62wihEhPvh49FIrYrMJ9vwHXpoG6/4MiQvhkldccqm2DcO7orS2CXejwN/TNZ+/R0MPQ1rkzGSW3PvhHnJK63j1ummMDPFpfcoc6ihDr9CNtILq3luIzfgRXj8LvrgbAobBLath2fsQNMIll2vbMLwrymobCfH1cJnGT4CXZuirOjP0AdGQsBC2vwnN3WcHDVaeXZ3KT2nFPHHJBM5MCGVMpD9pBcrQgzL0Cp1oaDaRXVrn+tTKgoPw3mXwn19AYzVc8TbctgZGznLpZb3cjSTHdt8wXCuWck3GDfTg0QPM+x3UFmlPOUOMz3bn8vr6Y9wwcyTXnTkS0GSys0vraGxRhfnK0Ct0IbO4BpNZus7QV+XD53fDa3Mhbzcsfhru2QETf+Gw3ry9zIjvvmF4iYvkD6z0aOjj5sLwM2HTP8DUxTGDkD055fzhswPMTAjhsYvHt24fE+mPySw5Vlzbh7PrHyhDr9CFdFd1lWqshrV/hhenwYEVMPse+M1emHU3uLnOe+6MlLjuG4a7Sv7Air+XFvuvaujCiAsBZz0AlSdg/39dNo/+REFlA796bxeRAZ7887oz2nUCszodKk5vQytBhcIWUguqcTcK4sL0K1SioRL+OVvLjZ94BSx6VFNr7COmtWkYPntUWIf9rjb0bkYDfp5uXXv0AKPOgejJsOFvMPkaMBhdNp++pqHZxK/e20ltYwvv3Tqnw3/7uFBf3I1CxelRHr1CJ9ILqkkM97O5t6pNHPlSM/LXroAr3upTIw9a6KSrhuGNLSZqGltcGroBCPByo6q+G6kDIbRYfVkmHFrp0rn0JVJKHvrsAPtyK/n71VM6DRl6uBlICPNTHj3K0Ct0Iq2gWv/4/IFPtObeo8/Td1wnSIkLZvfxCppN5nbbXZ1DbyXA2717jx5g7MUQlqR59WZz98cOUN5Yf4yVe/L4/XljOG9CVJfHjYnyV7n0KEOv0IGqhmbyKxv0NfQ1RZD1M0y8vNcWW22hq4bhpS6uirUS6O3eeXplWwwGzasvOgRbXnLpfPqCdalFPLM6lSXJ0dy9cFS3xyZF+nGirJ7axqEt+KYMvcJp0gtcsBB7aCVIM0y6Ur8xdaCrhuGuFjSzEuDt3vVibFsmXQHjL4EfHoONf3fpnHqTjKJq7v1wD+OjA3juisk91ixYG+AcLRrajVmUoVc4jfXRWFeP/sAnEDkRIsbqN6YOdNUwvMzFgmZWAm0J3YC2CHv5v7UnojWPaxIRA5zKumZue3cnnu4G3rxxOt4ePS80t2beDPEFWZV1o3Ca9IJqfD2MDAvy1mfA8mzI3Q6L/qjPeDozIy6EH48UYjZLDAbNo7QqV/ZG6MYmQw+aVv1lb4DBXZOIMDfDgof6VSjMHl5ce5S8ino+umMmMTbea8ODffByNwz5OL3y6BVOk1pQzZgof/1K/w9+qv078XJ9xtMZa8PwYyWnwgFltY0YDaK1qMlVBHi5U9dk6rAY3CVGN7j0nzDlevj5L/DjnwaswuW2rFJS4kM4Y6TtonUGg2BMpP+Qz7xRhl7hFFJK0gur9ZUmPvCpVuEZPFK/MXWktWF41imBs7LaJoJ93Fs9fFcR6G0pmrLVqwctjLP0JTjjZtj4N/jh0QFn7OuaWjhyspppI4LtPre3NW/25JTb/kPcSyhDr3CK4upGyuuaWxe9nKbwsJYtMvEKfcZzAa0Nw9vE6UtrXFssZSWgJxmErjAYYMkLMON22PwSrH5oQBn7/bmVmMzSIUOfFOlPUXVjtxLTerE9q4zL/rmZa97YysnK/iMupwy9wil0X4g9+AkII0y4VJ/xXIC1YXhbgTNXV8VasYaGqhocSBcUAi58DmbeBdtehW9+P2Dy7HfnaE9PU4YH2X3umF6UQjhyUku7PZhfyUUvbuSntCKXX9MWlKFXOEWanqmVUsLBzyBhPvhFOD+eC7E2DM+3NAwvq20i1M/12js9Cpv1hBCaINyc38COf8FX9w0IY7/7eAUJYb4EO/Bjar0303shxTKjqAZ/Lze+vnceEf6e3Pz2Dl788ajLr9sTytArnCKtoJowP099jFzBAa1L0vj+681bsTYisYZvSmtdq1xpxRq6sStGfzpCwDlPwLzfw+53YdU9WhOXfoqUkj055Ux1IGwDEBngib+XW6+kWGYW15AY7kdiuB8r75rDRZOi+dsP6RRU9m3vWmXoFU6RXlhNUpROrQMPf6H1fNW5ubcrGBcdgJ+lYXizyUxlfXOvhm4c9uitCKGJxC14GPa+D5/fCab+WT2aU1ZHaW0T00baH7YBLdSWFNk7UggZRTWtrTS9PYzcuSARgC3HSlx+7e5QefQKhzGbJemFNSxLGa7PgEdWaZrqvh2VIfsbbRuGl9f1Tg496GjorSz4f1pWztonwT8Kzv2TPuPqiDU+78hCrJUxUf58uS+fphYzHm6u8W+rGpopqm4kMfyU4zO+6SCveb1M4PowqBgPfuEQNRlip/dqPUOPn1gIkSSE2NvmVSWEuK/N/t8LIaQQIszytxBCvCiEyBBC7BdCTHPlB1D0HSfK66hvNumTWlmUCiXpMG6p82P1EilxwaQX1rQ2tnC1/AGAp5sBD6PBNhkEWznr95C8DLa9ATXF+o2rE7uPV+Dn6eZUZtd54yOpbmjh24MndZxZe6z3gdWjp+Aghg+vZq7hIGPLf9LqGL7+Hbx1Drw6W/vvXd95bwO96dHQSynTpJRTpJRTgDOAOmAlgBBiOHAukNPmlAuA0ZbXHcCrek9a0T9ItcQ8dUmtPLIKEDDuYufH6iWscfrvDxUCrpc/AC0MEWCLsJm9nPUAmBr7pQja7pxyJg8PxOhEjcJZo8OJC/Vh+Zbjne7fnFnC6z9n8vQ3R/jtir088PE7ESrGAAAgAElEQVQ+iqsb7bpGhmWxNzHcV+uI9sFV4OnH6nmfMLXhNU7cfRx+ewQu/ofWNOfbB+CvY2HTiw5/Llux9xlmEZAppbT+1/o78CDQNiH3EmC51NgKBAkhop2fqqKvaGg2cff7u8ksbp+1kK6noT/8hVYk5d+15Gx/Y/LwIDyMBr47VABAqIsliq0EevfQfMQRwkbBhF/A9n9BXdd9cXubuqYWUgscK5Rqi8EguGFWHLuOl3Mwr7Ldvm3HSrn2zW3837epvLs5m23Hyvhibz4PfLIPaUetQWZxDe5GwQhfk2bkGyrh2hVMHq+1N9ycXQkBMVrh2h0/wR0/w+RlvdJnwV5Dvwz4EEAIsRTIk1LuO+2YYcCJNn/nWrYpBijphdV8feAkb2/Karc9rbCa4SHe+Ho6udRTmgmFBzW1xQGEtWF4niXFsjc8erAoWHbXfMRRzvo9NNfC1n/qP7aD7DvheKHU6VxxRize7kbea+PVt5jM/HHVIYYFebPn0XNJffJ8Nv3hbB6+cCw/pRXz/racbkZsT0ZRDYkhnrh9dqtW+HflOxCdzKgIP8L8PNmcWdr+hJgpcPELMN714UqbDb0QwgNYCnwshPABHgEe6+zQTrZ1+FkUQtwhhNgphNhZXNz/4oKKU1gFu77ef7JdaXdaQbU++fNHVmn/DqCwjRWrHIIQEOzTWx69HcJm9hAxTlsj2fZ6r8WOe8KZQqnTCfR257Jpw/h8bx4VlgX05VuOk1pQzaNLxhPs69Gq13TjrDjmjQ7jqa+PcKzYtvz7nKIy/mJ6HjJ+gIueh9HnAlq4bXZiKFsyS+16QtATezz6C4DdUspCIBGIB/YJIbKBWGC3ECIKzYNvm4YRC+SfPpiU8g0p5XQp5fTw8HBH56/oBaxNNcrrmtlwVPtRbmwxkVVSq09F7OEvIGYaBOmUvdOLWPXpg7zdnYoh20OAl42a9I5w1gPQWAXb33TN+HayJ6fc4UKpzrhx1kgaW8ys2HmCouoG/v5DOvPHhLN4QmS74wwGwXNXTMbDzcD9K/bR0oN2TXNdJY9X/ZHJdZvhwudh+i/b7Z+VGEpRdSOZlgVbK+mF1T2OrQf2GPprsIRtpJQHpJQRUso4KWUcmnGfJqUsAFYBN1qyb2YClVJK1y11K1xOWa22KOXn6cbne7Tf7GPFtbSYpfPx+YocyN/TK4+vrsDaMLy3wjbgQo8eIDoZxlwAW1+Bxr5VfJRSsjunwuFCqc4YGxVASnwIy7cc5+mvj9DYYubxpRM6VV6NCvTiqcsmsu9EBa+sy+x60LoyTO9czAyRyo5pf4GU2zscMjsxFIAtmafy6fMq6rni1c386avDzn+wHrApuGoJ1ZwL/MqGw78BLgQy0DJ0bnF4dop+QWlNEx5uBpZOiWHl7jxqG1tadUPGRgU4N/iRL7V/B1BaZVsCvd2ZEBPgcnni069ZVd/cTg9fV876PfxrkSYXfcbN+o9vI8dL6yhzolCqK26aFcfdH+wmt7yeexaOIj7Mt+NBZhPUV7AkppbMMaUcXvchOSKSEZ71UFcK9WXaonVdGZRl4l5fyR3N9/Obacs6veaIEB+GBXmzObOUG2bFYTJL7v/vXkxmya1z43X9fJ1hk6GXUtYBod3sj2vzXgJ3Oz0zRb+hpKaJMF8PLp0yjA+25fDD4ULSC6txM4jOvyT2cGglRE2C0ER9JtsHvHzNtF7t5RHg7YZZQm1TC/5eLviBGXYGBI6A9O/71NAfsGTH6BGfb8t5EyKJCvDCaBCd95zNWAMrboImLTb/GwB3YINlv9ETfELBJ0R7xc3jC/cL+XGrDy+Gd14lLoRgZkIoa1O1hjWv/ZzJ9qwynr9yMiNDnfwO2YCqjFX0SFltIyF+HkwfGcywIG8+35uHUQgSw/2cqzIsz4bcHXDO4zrNtG+Ic/bHzk7aVse6xNALoS0k7vsIWhq1nO8+wJrNNCLER9dx3Y0Glt+agrvR0LEdYXk2fHIrBI3QfuS8NWO+r8zAXZ8dZ/GMCTz2i45VrRv/u5fowNJuM9BmJ4by6e5c/rvzBH//IZ0lydFcPq13EhKVoVf0iCbY5YnBILh4cgxvbjhGoLc7c0Y5KVVwaKX274RfOD/JIURbQx+rX/i6PaPPg51vwfHNkLjQRRfpnvyKegK83FzyY9bp2lJzA6y4UVNRXfY+hCS07poMXFB0mH9tzGLexGIWJrVXV7WKmXXHLEuc/uGVB4gJ9Oapyybp15WtB5SomaJHSmtOKTNeOjUGk1lSVttEUqSTYmYHP4XYGf22k1R/JcDLqmDpQhGy+HlaiOLoD667Rg/kV9Tb3BtWF775PZzcB794o52Rt/L7xUkkRfrz4Cf72zUxkVKSWVx7SvqgC2KCvIkL9UEAf796Sq+u6yhDr+gWKSWltY2tVZ9jowJatW2SnFmILU7XZIn7aV/Y/ozDXabswcNXE5g7+r3rrtEDeRUN+jWc74ld78Ke9zTp5qTzOz3Ey93I36+eQkVdEw+vPNCaE19Y1UhNY4smfdADD104jueumExKvO19b/VAGXpFt9Q1mWhoNrfTm79s6jCEgHHRTqRWHvoMEANCe76/carLlAsNPWjhm9KjUHbMtdfpgl7z6Cty4NsHIWEhLHy420PHxwTwu/OS+PZgAZ/tzgPaatz0/IS7eEIUl58R6/yc7UQZekW3lFkeUdvmid86N55Vd88lNtjBRTIptbBN3FwIUDJI9qJL8xFbsFR2cnSNa6/TCTWNLVTWN/eOoV/7lPbvJS9rks09cPu8BFLiQvjjqkOcKKtr1YDqKXTTlyhDr+iWkhqtWCqsjWCXm9HApNhAxwctOKBJEk9Ui7CO4O/phhAuDt2AlvIaktgn4ZuTloybmCAvF19oH+z/L5z5awi0zdM2GgR/vWoyAL/7eB/phdX4e7oR7t832Um2oAy9ndQ3mVhzuJBX1mXQ2NJ/26/pxSmPXseb+OCnWgPwcQNLxKy/YDAI/D3dXO/Rgxa+yd4ATXWuv1YbrKmVLo/R//BH8A6CuffbddrwEB8eXzqB7VllfLwrl8QIv17LoHEElV5pI2sOF/LRjhNszCimoVnTpogL9eWi5MEderDq3OjWPcnaADxxIfh2WYOn6IFAHxfKILRl9Lmw7VXI3ghjznP99SzkV2g9Vl0ausn4EY6t05qle9tflHX5tGGsOVzI6kMFNsXn+xLl0dtAYVUDt7+3k0P5lVw9fTjv3DIDHw8j27JKez55gFNi0bnRTWs9dwdU5sDEK/QZb4jSk96NlJIfDhe2Uxt1iJFzwN2n18M3+RX1GA2CCFeFQ8xmWPNHrTBqxm0ODSGE4OlfTGJMpB/zRvfv9pfKo7eBTRklSAlv3jidicO02PT0uBC2Hhv8hr6spglvdyM+HjrdKjveAnffAdEAvD+jKVh2nUd/+GQVty/fyZOXTuSGmU7UKbh7Qfx8OPodyOd6rc9pfkU9UQFeuBld5Ise+FhbK7r8Lacqf0N8Pfj+/vk6Tsw1KI/eBjZllBLs48746FN542fGh5BeWNO6WDlYKa1t0s+bry7Q4vNTrwcvJ8XQhjg9efTW0Mf3lu5XTjHmPC0FseCA82PZSF5FvesWYs0m+On/IHrykKnKVoa+B6SUbM4sYXZiWDulwJkJWnx5e1b/abtmDzuyy7j+X9toaO5+QVmTP9DJ0O/4F5hb4ExbRFAV3RHg1X3f2IIqzdBvySylss7JWP74S8HgrmWn9BL5lS7MoU/9CsqzYN7vwDA0TODQ+JROkFVSy8nKBmaPar9wmBwbiLe70eXhm+1ZZS55avjvjhNszChh74nuOwmV1jS2K5ZymOZ62PlvSLpgQCtV9hd6Wowtshj6FrPkx9RC5y7mEwJjFsP+FWByoeyCBZNZUlDZ4DpDv/klrU/r2CWuGb8fogx9D2zK0BoFzElsv9jibjQwPS64R0NvMksuf3Uzf/h0PzWN9n1JTpTVseyNLbz+czdNDxxASsnGo9rn2tHDE0lbnRun2L9C0/GeeZfzYykI9HanscXc5RNZYVUDEf6eRAZ4tjYvd4rJ10BtEWSudX6sHiipaaTZJF1j6HO2aQkBs+6xqThqsKAMfQ9syihlWJA3I0M7VoHOTAjtMU6fU1bHruPlfLTjBBf+YwO7jpfbfO23NmZhlpBVom8Oc0ZRTeuj/fbsrg29lJp4WYizMXopYeurEDlJq4ZVOE2Al7Y43pUMQmFVI9GBXpw7PpKf04upb3Ky5mP0eZpk774PnBvHBqw59DGBLojRb34RvIJgyrX6j92PUYa+G0xmyZZjpcxODO20GMKWOH1aQRUAjy0Zj1lKrnxtM3/7Ib3HtLfKumZW7DwBQE5ZbbfH2st6izd/9tgIdh8v77JnZXVjC00mM2HOFksdWwfFR2DWXb2WtTHY6UkGobCqgYgALxZPiKKh2cx6S69fh3HzgElXQOo3Lm8cnt9aFauzR1+aCalfa+mUHr3bQ6CvUYa+Gw7nV1FZ39yl7rotcfojJ6sxCLgmZQTf/GYel04dxos/HuXK17aQVdK1Af9gew51TSbmjAolp6xO1+7xG48WkxDuyyVTYqhtMnHkZOe9QcusxVLOevRb/gm+EUqpUkcCe1CwLKxqIDLAk5kJoQR4uekXvjE1nuoj4ADvbT3OzW9vJ7ube99lhn7LK2B0h5Q79B13AKAMfTdssjTytTb2PR1rnH7bsa49+tSCKuLCfPH2MBLg5c7frprCy9dOJauklote3MBH23M6GPGmFjPvbM5izqhQzrd4ZMXV+izINraY2HqsjHmjwlqlUrsK35RaiqUcbnxtaoF1T0PGD5oX1UedigYjpzz6jus+jS0myuuaifT3wt1o4Jxxkfx4pMj54qmYqRCWBPs+dOj0qoZmnl2dyk9pxVzYxb0PWmqon6dba3hKF2pLYe8HkHw1+EfqN+4AQRn6btiUUcLoCD8iArqOFc5MCCWtsJrSLuL0qQXVrfrtVpYkx7D6vnlMHRHEHz47wB3v7Wp3/lf78ymsauS2eQkMt7RRO16mT5x+9/EK6ptNzBsdTnSgN8OCvLtckC2xePRhjmTdVObB8qXw819g8rUw515npq04je48+qIq7V6KtNy3502IorK+2flUYCFgyjVwYpsWBrGT97Ycp7qhhTdvnN7u3i9r08QDTuXQ66ods/MtaKnXFmGHIMrQd0Fji4kd2WU9tsvrLk5f29hCTlkdYztp0BEd6M17vzyT/71oHD+nFbP4hQ2sSytCSsmbG7IYHeHHgjHhrY2Dc0r1MfQbjhbjZhDMtDylpMSHsPN4WaeeVWcSxTaRthpemwv5e+Gy1+GyV8G9FzsFDQFau0x1shhbVK0ttEdaFjPnjwnHy92gT/hm0lWA0PrJ2kFdUwtvbcxiQVI4546PbHfvP/xZ+0Is3XXoWxph+5sw6hyIGKvfuAMIZei7YPfxChqazT0a+u7i9OmF1UhJB4/eisEguG1eAqv+Zw5hfh7c8vYObn13J0dOVnHbvHiEEAwL8sYg9PPoN2aUMG1EMH6WJsYz4kIoqWnqdL3A+pRhs6FvaYLVD8GHV0PgMPjVepi8TJd5K9rT6tF3UgxVUGn16LUnMW8PI2eNDuf7Q4WYzU6u9QQOg4QFWvjGbHsmz4fbT1BW28Q9C0cBp+79G2aNZG1qUbsnE90N/YFPtNTQWXfrN+YAQxn6LticWYJBwJkJ3bf8OpVP39GjTy3QFjk78+jbMjYqgM/vnsNtc+NZm1pEmJ8Hl0zRusN7uBmIDvQmp9T5zJuy2iYO5FUyt40AU0q81l16Rydx+tLaJvw93fBytyHfuOwYvHUubP2ntth16xoIG+X0nBWd4+FmwNvd2GnoptCSOhvpfyrkuHhCFAVVDezPq3T+4tNugMoTkLnOpsMbW0y8sT6TM+NDmB7X/vu0JDmaJpOZHw5rRV31Tdr6gm7yxFJq92TEeK2D1BBFGfou2JRRQnJsUOsjcnfMStTi9AWVDe22pxVU4+thJDa455vWy93I/y4Zz2d3zebtm1PaGdcRIT7k6ODRW8XZ2irtJYb7EeLrwfasjvn9pTU25tAf+AReOwvKs+Hq9+HC5zQxLIVLCfB26zR0U1jdgIfRQJDPqXt30bgIjAbB6oM6hG/GXgw+YbDrbZsO/3RXHoVVjdxzdscf/inDg4gN9uar/fmAJn0AOjYcyVoPhQe1Qr0hnNqrDH0nVDc0sy+3kjmjbNNLP3tsBADr0orabT9ysoqkKP92Gjk9MW1EcIfuTSND9TH0G4+WEODlRnLsKe1tIQTTRwZ34dE3dl8V21QHq/4HPr0VIsfDrzfCuKFTVt7XdCVsVlTVSESAZ7vFzCAfD2YmhPD9oQLnU3XdPGDqdZD2LVSd7PbQFpOZ137OZHJsIHM7CYMKIbgoOZqNR0sor206lVoZqJNHv+UV8A2HSVfqM94ARRn6TtieVYbJLDvIHnRFUqQ/w4K8+fHIKU0RKaWWcRPtvErjiFAfSmqaqLVTQqEtUko2HC1mzqgwjKf98KTEh5BTVtf6yG+ltKap685SRUfgzbNh93uaONTNX0PQcIfnp7Cfrgx9QWUDUZ1kii2eEMWxktrWZtZOMe0mkCbY859uD/tyfz45ZXXcvXBUl1k0FyfH0GKWfHeoQN8c+pKjmrzy9FuH/BOmMvSdsCmjFE83A9NGBtt0vBCCReMi2JhR0qo9UlDVQGV9c5cLsfYwwpJi6YxXf6yklvzKBuaNDu+wb4Ylbnp65lBpbVO7XrFUF8DeD+GzO+CNhZp2zQ2fwaLHtEIURa8S7OPRmgLblsLqhtbUyracNz4KQJ/sm9BETad+97tdLsqazZJ/rsskKdKfc8Z1nbs+ISaAuFAfvtp/kryKBoSAKD3kD7a+CkYPmHGr82MNcHqsSBBCJAFt9UkTgMeAYcDFQBOQCdwipaywnPMQcCtgAu6VUn6n87xdyubMEqbHBdu2CGlh0bhIlm85zpbMUhaOjbB5IdYWRoZoKZZ5hUWMO/ISVOdDYzU0VIGpCTz8wNMPPP21926e4ObV7t+8Y9VcaCjiXGMzZGZq2/0iIDSRCTEB+HgY2ZldxsWTYwDtS1pu1aIvPw4f3wT5e7QJ+YRpjb3PeVwbQ9EnjI7048fUIhpbTHi6nbpXi6oamT+m45NYVKAXU4YH8d2hQu45e7TzE5h+C3x8s9aSr5M2g98fLuBoUQ3/WDal2/ClEIIlyTH886cM3I2itdDLKaoLLQVSV6l7FBsMvZQyDZgCIIQwAnnASiAJeEhK2SKE+AvwEPD/hBDjgWXABCAGWCOEGCOlHBCdtIurG0ktqObB85PsOu/M+BB8PIysOVKoGXqLrECSTh69Dw1MXHcrVO0HvyitcYenPxg9oaYQSjM0499Uq5Wpm9uHec4CzvIAvjpt8HEX47bocaaNCGZTZilSSoQQVDU002KWRLvXwX+ug9piOOcJSDwbIicOGR3v/sy46ABMZsnRwprWzmc1jS3UNLZ06tGDFr75y+pU8irqnc9sSbpIi3/veqeDoZdS8vK6DOJCfViSHNPjUEsmR/PyugzWpRUzbYT9/VvbkbZaWzuSpiFbIHU69tYYLwIypZTHgeNttm8FrE1ALwE+klI2AllCiAwgBdji7GR7g82ZncsS94SXu5F5o8NYm1pkic9XERPo1Zrv7AyBbs286/U84ZVpcNU7MP6Snk8ytWgGv6WRpoY6lr6whgvHBXPv/BFaAUlLA+Rs1bS5U7/h0djLub5oAQfyKkmODaKkpglvGrjwwG+gOhdu+BxGznL6syj0w/q0eORkVauhb02tDOh8bWXxhEj+sjqV7w8VcMuceOcm4OYBU67T7qGqfAg4ZdB/Ti/mYF4Vf7l8Uoc1oc5IivQnMdyXzOJax+PzDVXw3UPaukHkRC2sGDHOsbEGGfa6ZcuAzoQufgl8a3k/DDjRZl+uZduAYHNGKQFebq1fHHtYNDaSk5UNHD5ZRZpOC7E018NH1zCNVF4PfdA2Iw9gdNMU+nxC2FPhTWpTOEnJZ2p6JSNmakUvC/4A9+6B6bcwJu8zNnnei/z0Nji+mfLqWl52f4ngioNaX01l5Psd8WG+eLkbWsOE0NbQd+7RJ4T7MTrCT584PcAZlkXZNU9oWVgWXlmXQUygF5dNjbVpGGv4BnDsSSNrA7w6RwvXzP0t3L4WoibZP84gxWZDL4TwAJYCH5+2/RGgBXjfuqmT0zvkcwkh7hBC7BRC7CwudlJCVUc2ZZYwMyHUJi/kdBZa0iy/O1hARlGN8wuxZhOsuAmO/cz7kQ+wouFMh4bZmFGC0SCY1Zk4m18EXPRXxN3b2RJyCfHlm+DtC5j83zNZZNxDwZw/q5TJforRIEiK9OfIyarWbafr3HTG4glRbM8q66Ax4xAhCVp4ZP9H8MqZkPoN246VsiO7nDvOSsDDzXZf8uLJMQih/YDZTHM9fPsHeHeJlhDwy+/gnD8qAb3TsMejvwDYLaVszSEUQtwELAGuk6eSc3OBtnl2sUD+6YNJKd+QUk6XUk4PD++YCdIX5JTWkVte36PsQVeE+3syeXgQ7209TotZOu/Rb3lFSw+78DkK4n9Bbnk9JgdK2NcfLWHK8B6Kv0ITcb/oWVIaXmHP1D9T7pvAX5qXYUxRGQv9mXHRARw5WdWaG9+TRw+aoTdLWHPEyRaDrQM+BTd/oz1BfnQNHiuuIdm3nGUpI+waZlSEH9/+Zh6XTbMxAJC7C16bB9te1aqxf70Bhqc48AEGP/YY+mtoE7YRQpwP/D9gqZSybd7fKmCZEMJTCBEPjAa26zFZV2OVJba1UKozFo2NoNyiP+KUR19wENY+qfW1nHEbI0J8aDHL1jxjW6moa+JAbkW7atiumJkQSlhwEM8Xz+CjCa/zqmkpwXo1Ble4hLFR/pTXNVNo8eQLqxrx9TC2ahl1xsRhAQwL8uY7PapkrcTNgV9vID/lEcbU7+Uz+Vu8Nv9NWw+yg7FRAe0yiDqlpQnWPqVJbjTXaetHFz435JqJ2INNhl4I4QOcC3zWZvPLgD/wgxBirxDiNQAp5SFgBXAYWA3cPVAybjZllBDh70liuJ/DYywap4VvPIwG+x5B29LSCCt/BV6BcPE/QAhGhDqWS785sxTzabIHXWEwCK48YzibMkrZl1tBoLe782luCpcyzvLUeMTSyUxrONJ9DroQgnPHR7Iho8TuPsbdYnTnjyVnc6l4ATnmfFj3Z/jnLH37zBYehn8tgvXPatryd26GxKGrYWMrNn2LpZR1UspQKWVlm22jpJTDpZRTLK9ft9n3lJQyUUqZJKX8tvNR+xdms2RzZilzRoU5pYM9PjqA6EAvEiP8HDeS657W9DmWvgy+moF2tGhqw9Fi/D3dmBxrW8ra5WcMQwhYm1qkT1NwhUuxhgetcXpbDD1o4ZumFjM/p+m3PpZaUMUPhwu5YM503Jcth+s/AyS8d5mWb1/VIYJrO1JqncremK+Nc/X7mvy1t5OpmEME5a5ZSC2opqy2yeH4vBUhBM9ekcyjSxxM68reBJv+oZWYJ53fujk60Bt3o+C4Hbr0UkrWp5cwKzEUNxt/dGKDfVo1SZxuIahwOYHe7gwL8m5tB6lVxfa8EDkjLpgQXw/9sm+Af67LxMfDyC2z47QNoxbBnVtg4SOaLs7LM2Dzy2DqvP1hl9SWwofLtNTJUefAXVtVgoCdKENvYbMO8Xkr80aHM9vOPHwaquCHx+C9SyE4DhY/3W630SCIDfbhhB0efXZpHXkV9cwbY99i91XTtbX0UGebgit6hbYLsoVVjTZ59G5GA+eMi2BdahFNLU62GASyS2r5an8+188c2X5dx90L5j+oGeeRc+D7R+DtC6C5oevB2nJ8s9bEJnMtXPAcLPsA/PpH8sZAQhl6C5sySkgI8yVaL9U8WzGbYPdyeOkMzZOfeAX8crUmaXAaI0J8OF5muy79xqPaY/k8O59Szh0fSZifZ+u6gKJ/My7an2PFNRRWNdLUYu629WVbFk+IorqxpdXJcYZXf8rEzWjgtrldFGGFxMO1/4VLX4PcHbDm8Z4HPfQ5vHOR9mNx2xo4844hLTXsDDp23x24NJvMbM8qsz2tSy+yN8HqP0DBfhg+U/siDJvW5eEjQ33YnVPeKlPQE+uPljA8xJuRdhpsL3cjq++b123mhqL/MC46ALPU1mOg66rY05kzKgxfDyPfHSpkQZLjejD5FfV8tieXZTNGdP8jY+05m79HS4lMPLtTjRxAU0f9/C4YdgbcsFKT+1A4jPLogX0nKqhtMtkte+Aw5dmw4kZ450KoL4cr/q158d0YedA8+uqGlk6laU+n2WRma2Ypc0eFO7S4HObnaZeom6LvsGbe/JSuGfrOJIo7w8vdyIKkCH44XOhQfYaVN9YfQ0r41fwE204490+aRMHnd2qKqKfTUAkfXaelS171njLyOqAMPVrlqBB0XjmqJ43VWqn4yylw9AdtkeqeHTDxcpseSa2ZN7YsyO47UUF1Ywtn2ZBWqRjYjAzxwdvdyIZ0q0dvu8TveRMiKalpZE9Oxw5jtiCl5Iu9eVwwKZrYYBufHN29NFmNplotjdjcZo3AbIbPfgUVx+GqdyEg2qF5Kdqjns3R9G0mxAQQ5OOiLBOzWWum/OMTmtJk8jJNwz3QvlDR6EjNszmUX8Xk4d2nla0/qvW8tXtRWDHgMBgESVH+7D1RAWgV2raycGwE7kbBd4cKOvRztYXCqkbK65qZbmPvhlYixsL5/wdf3QfvXw7RkyE4HopTIf1buOBZGDnb7vkoOmfIG/q6phb2nCjnl84q+XVFVT789wbI2wmxM7SsgdjpDg0VF+pDhL8nW46Vcu2Z3ZeXbzxaTHJsEIE+qiHIUGBcdAB7T1QQ5ONuV8gtwMud2YlhrD5UwMMXjrM7zGct1HKoCvyMm6E8C458pYmSmX9GEbUAABnGSURBVC0hyeSrNUkDhW4MeUO/PauMZpN0On++UwoOwPtXQWMVXPY6TLrKKR13ITRhsk0Zpd0uyFbWN7P3RAX3LOzYjFkxOBkfrRnaSH/7OzMtnhDFwysPcORkNeNj7NNnSnOmwY4QWrz+3D9p2WeVuVBbAjFTVHaNzgz5GP3mzFI8jIbWdnq6kf49/Pt87Yb95XcweZkuzTpmJYRSUtNIZnHXfT+3WGQP5nbSNlAxOLEuyEY60ILv3PGRCAE/HLZf5Cz1pKXvgrNPjgYjBI+E2DO09wpdGfKGflNGCVNHBOHtodPNVV0APz0DH16tSbje9iNETdRnbE4tGG/JLO3ymA1Hi/H1MDLV2U49igGDtZNZpB3xeSvh/p7Eh/mSWlDV88GnkVpQrUsXNYVrGdKGvqy2icMnq5wP25ia4dBKeP9K+Ns4+On/YOxFcMu3umcNjAjxISbQiy3HujP0muyBEiQbOvh7ufOr+QmtPX/tJTbYh9xy+5RRm1rMWt8FPRrsKFzKkI7Rb8ksRUonZQ+aauGja+HYT+AfA3Pvh8nXQphr4uNanD6MtamFmM2yQ9Pl46W15JTVcWtXFYqKQctDFzjeNm94sDcHcivsOiezuEbru6A8+n7PkDb0mzJL8PUwkmyjsmMHGqrgg6vhxFZY8gJMu7FX4ouzEkP5dHcuaYXVrbFZKxuOauXsc1X+vMIOYoN9KK9rpqaxxeaKaGuo5/R7UNH/GNLP9pszSjgzwcEQR325JkCWu10r/ph+S68tInUXp994tIRhQd4kOKqFrxiSDA/RNJ5yy20XzUstqHau74Ki1xiyhj6vop7s0jpmO1IN21AJ716spU9etRwm/kL/CXbDsCBvRoT4dIjTt5jMbMosYd5o5zT1FUMPa1XriTLb4/SpJ6sZ5UzfBUWvMWT/D324LQeABUkOpCBufEFr9bfsA23RtQ+YlRDKtmOl7TRK9udVUt3QosI2CruJDXbEo69ibLSKzw8EhqShP1lZz5sbjrF0cgyjIuy8UWtLYNvrmhc/+lzXTNAGZiWGUtXQ0tpZCODntGKEoPfE2RSDhlBfD7zdjTZn3pTVNlFY1cg4RwqlFL3OkDT0z32XhgQeWJxk/8kb/w4t9bDgId3nZQ9t4/QtJjMv/niUV9ZlkBIXohp6K+xGCEFssLfNjW2sC7HKox8YDLmsm4N5lazck8cdZyUwPMTOxhpVJ2HHvzQtjrDRrpmgjUQGeJEQ5stXB07y1YGT7DtRwdLJMfzpkgl9Oi/FwCU22Ntmjz71pBPSB4peZ0gZeiklT319hCBvd+52RAdm49+04qj5D+o/OQeYlRjK+9tyCPJx5+Vrp7Ik2bFiGYUCYHiID7uO2yZXnFZQTZifh11KmYq+Y0gZ+rWpRWw5VsoTSycQ4GWnNkfFCdj1Dky9TpM26AfcMicOTzcjv56fYHP7OIWiK2KDvamyNLYJ9O7++5FaUKWkDwYQQyZGbzZLnv7mCAnhvj1K/HbKhudBSjjrAf0n5yCjIvx57OLxysgrdMGaYtlT5o3JLEkrrFZhmwHEkDH02aW1ZBbXcvu8BPvzfne9ozXwPuNmCHLgR0KhGAAMtzGX/nhpLQ3NZiV9MIAYMqEbq272xJhA20+SUlOi/PkZGHUunPO4S+amUPQHbM2lT7V8l5T0wcBh6Bj6wmqEgFERfradYGrR2pzteQ+mXA8XvwBG1a1JMXgJ8nHHz9Otx8yb1JNVGOz5Lin6nKFj6AuqiQv1tU13vqkWPr4Zjn4PZz0ICx9WHW8Ugx5rLn1PHv2RgmoSwv3salmo6Ft6DFYLIZKEEHvbvKqEEPcJIUKEED8IIY5a/g22HC+EEC8KITKEEPuFENNc/zF6Jq2wmqRIG2KKNcXwzhLIWANL/g5nP6KMvGLIYEsu/ZGTVSpsM8Do0dBLKdOklFOklFOAM4A6YCXwB+BHKeVo4EfL3wAXAKMtrzuAV10xcXtoaDaRXVLLmJ4Wj8qOwb/Pg6IjcPX7MP2XvTNBhaKfYG1AIqXsdH9VQzO55fVqIXaAYW/WzSIgU0p5HLgEeNey/V3gUsv7S4DlUmMrECSE0LfNkp1kFNVglj10qs/bBf86F+or4KZVMPbC3pugQtFPiA32pqaxhYq65k73WytixyuPfkBhr6FfBnxoeR8p/3975x6nZVXt8e9vGBguM9wRFQxM8YaoBXnJ6KJhmWWZaaSpkGUdTcuupqZG5imPlZdK02NpppmaHi+nU2IlaWYJph8REBHhAAJekGG4DAPM6o+9X3gZZpgZGOZ5ns36fj7vZ553P/sd1o/9zHr3Xnvvtc0WA8Sfu8TyIcCCss8sjGWZUVpxs09LoZsXJ4dwTbeecObDsMehnWid4+SHTWvpmw/flJLoeeimWLTZ0UvqBhwP3N1a1WbKthgHSjpL0lRJU1977bW2mrFV6tdt4NW6+i3KX1haR7fKCoYPaCa3zb9+HU6JGrA3nPlI5jlsHCdLSgeQLGhhQnbm4hX069mVwb099UGRaE+P/ljgaTNbGt8vLYVk4s9XY/lCYI+yzw0FXmn6y8zsRjMbY2ZjBg3ahpzwzXDVH1/gQ9c8xroNjZuVz1pSx96Dqqks3yhlBlOuhPvPgT3fDRN/DzWDO8QOxykqre2OLU3E+sE2xaI9jv5TbArbADwAnBGvzwDuLys/Pa6+ORyoLYV4djRPzVvG6ysb+MfcZZuVz15St2V8fsqV8JfvhUyUp9wFVT655Dh9enSld/fm19KXUh942KZ4tMnRS+oJjAPuLSv+PjBO0ovx3vdj+e+BucAc4Cbg7A6zdius29DIzBiLnzxjycby2tXrWLKifvMETM/8Bh69Ag4aDyf8HCo9f7vjlBjar2ezeennxdQH7uiLR5s2TJnZamBAk7I3CKtwmtY14JwOsa4dzF5aR8P6Rnp268LkGUu57PiRSOKFpXEituTo506BB74YwjXHX+dr5B2nCUP79eDl11dtUb5pItZHv0UjmaRmzy2sBULq3ldq63n+lfBQvlA6CWfXmrA+/renwYARcPJt3pN3nGbYo3/za+lnLl5BZYU89UEBScfRL6qlpnslE4/ckwrBwzPCnPGsJXXUdK9k18pVcPtJ0LU7nHoX9OibscWOk0+G9uvBmnUbeGNVw2blMxfXsdegaqoqPfVB0UjG0U9fVMuBu/dhYHUVY4b1Z3J09LOX1rH/4F7o3rNg5avwqTs91bDjbIWW1tKHFTcetikiSTj60kTsqKEhBfExIwczc/EKFixbzawldZyl++ClP8Gx34chuUi94zi5ZVjcb/LcotqNZctXN7C4tt4nYgtKEo6+NBF74JDg6McdENbD3/bkfEY1PMPRS26GUSfD6IlZmuk4hWDELtWMGtKHGx59ibXrNwAww3fEFpokHH1pIvbwlY/AzR9g2NQrOL3/8zz55ONc0/Un1PfZK2Si9BU2jtMqkvj6B/Zl0fI13PnPkM1k5mI/bKTIJJGP/rlFtfTuXsGgp66C+lp45WkmbWiAClhtVaw/8Vao8pUCjtNWxo4YyGF79ue6P8/hpDFDmbl4BQOrqxhU46kPikgSPfrpi2oZ338uWj4fjvshXLCAOR+6iyvXncw3u15AzVsOzNpExykUpV796yvXcssT83wituAU3tE3rA8TsR+3ydBzAOz/EejanbeOOYb7qsezaujYrE10nEIyZnh/jtpvF2549CVeXLrSUxMXmMI7+tlL6+izfhn7LH8MDjkFKsPQsqJC/OozhzLpoyMzttBxistXj9mHFfXradjQyH7eoy8shXf00xfVclKXKVTYenj7hM3ujRhcs3FNsOM47Wfk7n348EHh3CCfiC0uhZ+Mnb7wTb5Q+Rds+Fg0cO+szXGc5LjkIwcweli/tp257OSSwvfou8ybwlC9ikZPyNoUx0mSXWq6M/HIPT0HfYEptKNvWN/IEcsfZHVl3zAJ6ziO42xBoR393Jdf4mhN45XhH984Ces4juNsTqEd/cqZk+lCI1WHeWoDx3Gclij0ZOyY489m2TuOZcjg4Vmb4jiOk1sK7egB+u+2Z9YmOI7j5JpCh24cx3Gc1nFH7ziOkzju6B3HcRLHHb3jOE7iuKN3HMdJHHf0juM4iSMzy9oGJL0GzM/gnx4IvJ7Bv7sjcU35JzU9kJ6mougZZmaDWquUC0efFZKmmtmYrO3oSFxT/klND6SnKTU9HrpxHMdJHHf0juM4ibOzO/obszZgB+Ca8k9qeiA9TUnp2alj9I7jODsDO3uP3nEcJ3nc0TuOs1OinehsRHf0BUTSUZJ6ZW1HRyKpv6SKeF34P0BJ3cquU9AjSSdLGpC1LR3IxmPpUmijrZGso5f0OUk/k7RX1rZ0FJJOlTQNeB+wLmt7OgJJp0h6Bvgx8AMAK/DEkaTTJP0duFrS+VBsPQCSPgy8SHjuemRsznYjabykWYQ2+goUv41ao/AHjzQl9gpPAr4BLAYOk7TIzOqztWzbiD2NSuBLwEXAsWb2ZLZWdQySjgbOAc4FlgA3SRphZi9ma1n7iG1UBVxAcIZfB7oC35H0rJn9OUv7tgdJPYBPAJ81s0eb3FPRHKSkYcB5wGeAN4F7JL1uZr/K1rIdS3I9ejNrBJ4B3gFcD7wb2D9To7YRSV0tsA6YDdwOzJfUTdKJknbP2MR2Ux7SAA4GHjKzxwiOciHwaiaGbSNlbVQPPAecYGaPA48DfwMGZ2rgNtCkjboAfYFnJQ2U9HlJo6E4vWBJXcve9iT8LT1vZjOBLwNfldQ/E+M6iSQcvaQLJR0WrwXMNbPlwD2AgLGS+mVpY3uR9C3gZkkTJdUAfwH+H/g/4GngBOBWSRfF+rlvS0mXAndETRXAVOCDku4Afg/0A26XdEmsn2tNzbTRvcCbkiril/NBQF2mRraTsjY6Izq/KqABOAL4HTASuFbSD2L9XMe2y9pogqRqQshzF4LDx8wmExz/N2L9XD9z20qhRUnaTdLvCI30awi9DDNbF4eV6wgP52jg7U0+m8sHVNJ+kp4g/EHdDZwInGFmdcBjBEf/QTP7NHA+8DVJA+JIJrfEePW7CKOso4GrgWeBccAbhNDAccDXCD2sgXnV1EIbnQ6UeveNMeSxnjC6LARN2uj9wKXAKkII9CLgBjM7j6D1VEm757VX30wbfQKYYGZzgBXA58uqXwCMl9Q3r8/c9lJoRw/UAnebWV9geWliRVJl6QE0s4eBecAoScdJOieW5/IBJfQA7zKzT5vZg4Re4jvjvWnAZWa2EMDMpgN/IGTayy2SugBvA75jZn8CJgFrgG+ZWQMwlOD0MbNZwP8CQzIyty0010ZHmFlDWY+wN1BtZgslHSzplMysbQPNtNF3CT3584HLCKOtitiBeokQlhqRkbltobk2ele8913gBEljAKKeR4DqTCztBArt6M1sNcEpQHggL5LUzczWS6oo+6P7A3AhcBPQrZlflRvMbBHBzhL/AGokdTezBjNbCyHuKOk6gkPJIsVzm4iOYQOwFDgzFs8hhNVGStqN0GP8haR9JV0N7Aa8nInBbaCFNuojqaqsRzga6C7pMuAXhMnZXLKVNroLOBLoBVwFHA58QdKPgD2A6RmY2yZaaKNeknqZ2fPArcDZkr4p6XpgL8LIMkkK4+glNdvDM7O6+KA+DkwBbojljXEIPQj4L+BBYG8z+3GnGd0KW9G0quztUcCC8lVDkj4KPAFsAE7K04oiSYdK6l16XzZy+jkwVNLo6AznEWL0Ywlf0jOBa2Ld48xsRedZ3TJN9ZRooY3WlpXtT5hsrgLGmtmtO9bStiPpeJUtO26ljZ4C3gv8kpD/ZThhNDbOzHLhGJvqKdFCG5XKromv3YGVwIfNbM0ONzYrzCzXL0KscBpweZNysSlXT2X8ORhYRghlHADsF8sHZq1jOzRdDYyP16MJQ+hhwPCsdTSx/T3ADOC/gaFl5RXxZzfgm8Bvy+5dC5xVpr1X1jraoKe1NhpDCAGMAfbJWkczz93fgdeAd7WjjT7btG4eXlvR05a/o7fE6y5Z6+iMVy579Ap0k/QzwpDxu2Z2cdn9LhaJPfZKADNbSojFvQrcQlgahpllflLMNmgq7drrBQyS9EtCbLGPmc03s3mdraElJHUnrPOfZGaftTiHEDWVQhl9gNuAAZIujj2wfYF62DiJvqqZX9/ptKKntTaaROhYTDWz2ZkIKCM+d9WSHgQujq8nCZ2F0nxWa23UUPp9lvFkZRv1tKWNSr5hQ6eLyIKsv2m29iLE0S6L1xXAwU3u/wT4H0LvvQI4jTDc/HrWtneAphGEEcoaQiz0y1nbvhVNewE3xesewMeBQYRVKAA/A+4HdgUOBL5HCNtckrXt26jnpwVso/Fl118kTFSW3lcC1xWsjVrTc23R2mhHvnK1M1bSeYSY2b/M7LeEb94bJV1FGKYtkLQYuIPg0GuAiWb2Zvz8TOAQC2voc0EHaLoQuNXMlmVhf3OUaZpqZvcQ1ia/T9JYQg9rDWHJ4SxJNxJCGROipiWESfNJtnlMOzO2QU+R2miamd1tZnfG8grCjtAFcfJ4LcGxF6WN2qon923UqWT9TRO/gUWYkPsbYb3rTODMeO9c4CHCELKGMKT+OdC3/Bs8aw07QFPuYoetaPohMAt4f3x/AKEHNSKvmlLTsxVNE4BBZXXeCcxq4fO50pSansz+H7M2oKxBHgDeF68/SJgRPzm+ry6r925C77dXfAhyMzm0E2v6JGG5XQNhM1ep7g2EERZ51ZSanhY0/Rg4rUmdR4CPxuvSxGUuNaWmJ4tXp0/GSpvvSC1b615aaoeZ/YHQm3q7pH3NbGXZR8YBq4F6C2S+k801MZqw2/Bi4CuSRkr6NmEIvSDWzXwSr8n7QuuBdmmaTdizsF+s15ugsyHWKW0uLEobFUJPnshi1c1maU7LGmMOYWPQqPh+CmEVQA1sTC06nTC7fqHla7bcNcFbzexKQiqKc4C9CWv8c7HWmvT0QPs1Vcd6Kwi7kfOWcC01Pbmh0xy9pMMV8tL8VNIxCluukVSaEP4nYQPQuLhEagZhG/yYeH8+8B9mdrqZ5SLDoWvaqGk3QtIrLKR7/ZKZnWFmizOQsBmp6YEOee4grFq5pTPtbonU9OSRTnH0kt5LWGJ3L/AC8Gmgn0KWv/UAFpINPUXoOV0QP7qWuL3fzP5uIZ1tLnBNW2iaW/o9FpLJZU5qemC7Nc0r/R7LyW7q1PTklc7q0R8EPGVmtxOGwl2BlaWhmaTLJd1M2C16LXCowklKy4A/dpKN7cU1ba7p4Yxs3hqp6YH0NKWmJ5/siBleQvKjfcreH0JomEsJiZMeJSR6+iRhadQdhDw0pfrVlC01zMPLNeVfU2p6UtSUmp6ivDq6EfsSsknWEVYslC8hPDQ24Inx/ZmE7HIHl9XJ3XIo15R/TanpSVFTanqK9uro0E0vQlji3Hg9tnTDzP5J2EZeSqn759j4pZ1rFZbP5VCuKf+aUtMD6WlKTU+h2G5HL+l0Se+R1NtCDugbCXms6wkHc+8e61URUuueHT96NNCfTUmtctOQrin/mlLTA+lpSk1PkSntIGvfh8LGhl0J8bNG4CXCt/SXLGaKlHQkcDIhf8htsWwkIRa3KyGfyBctHNCbOa4p/5pS0wPpaUpNTzK0N9ZDzB0B7AP8Ol6Xst/d26Tu+cDlhGFYj1jWg7AZJfO4lWsqjqbU9KSoKTU9Kb3aHLqRVCnpCuAKSe8hJOTaAGBhvet5wBHxXombCLPkk4F5koaY2Rozm0sOcE0bya2m1PRAeppS05MibXL0sYGmEU43mkM4AKOUyvVQ2JhfYhLhIOESxxHibs8AoyzE6XKBa8q/ptT0QHqaUtOTKm3NR98IXGWb4mlvA/YELgGuB0YrJCC6j9DAwy2cgFRPSPP61w63fPtxTfnXlJoeSE9TanqSpK2hm2nAXYo5KAi5od9iIbdEF0nnWpgZHwpsiA2Jmd2f44Z0TfnXlJoeSE9TanqSpE2O3sxWm9la25RdcRzhQF6AicD+kh4CfgM8DVumHM0brin/mlLTA+lpSk1PqrTrKMH4rW2EdKAPxOI64EJCru6XS7G2GJfLPa4p/5pS0wPpaUpNT2q0d8NUIyHp0OvAQfGb+ttAo5k9XtAJFdeUf1LTA+lpSk1PUrR7w5Skwwm72J4AfmlmN+8IwzoT15R/UtMD6WlKTU9KbIujHwqcBvzIcnJC/PbimvJPanogPU2p6UmJbUqB4DiO4xSHLM6MdRzHcToRd/SO4ziJ447ecRwncdzRO47jJI47esdxnMRxR+84gKTLJH1tK/c/JumAzrTJcToKd/SO0zY+BrijdwqJr6N3dlokXQScDiwgJOKaBtQCZwHdCPnVTwMOAR6K92qBE+Ov+CnhUOvVwOfMbFZn2u84bcUdvbNTImk0cAtwGCG539PADYSt+2/EOpcDS83sOkm3AA+Z2T3x3p+AL5jZi5IOA/7TzI7qfCWO0zrtyl7pOAkxFrjPzFYDSCplXDwwOvi+hKPu/tj0g5KqgXcCd5dl3K3a4RY7zjbijt7ZmWluOHsL8DEze1bSBOC9zdSpAJab2SE7zjTH6Th8MtbZWfkrcIKkHpJqgI/E8hpgsaSuwKll9eviPcxsBfCypJMgHKQh6eDOM91x2ofH6J2dlrLJ2PnAQmAGsAr4Rix7DqgxswmSjgRuAtYCnyDkX78e2I2Qh/1OM5vU6SIcpw24o3ccx0kcD904juMkjjt6x3GcxHFH7ziOkzju6B3HcRLHHb3jOE7iuKN3HMdJHHf0juM4ieOO3nEcJ3H+DVWgiYoE7XgjAAAAAElFTkSuQmCC\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "import matplotlib.pyplot as plt\n",
    "df.close.plot(label='close')\n",
    "df.close.rolling(window=10,min_periods=0).mean().plot(label='ma10')\n",
    "plt.legend()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "rolling函数也可以接受一个指定固定大小时间补偿字符串，而不是一组时期。这样可以方便处理不规律的时间序列。这些字符串也可以传递给resample。"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 92,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.legend.Legend at 0x22e2ff40c18>"
      ]
     },
     "execution_count": 92,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "df.close.plot(label='close')\n",
    "df.close.rolling(window='20D').mean().plot(label='ma20')\n",
    "plt.legend()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# 指数加权函数\n",
    "另一种使用固定大小窗口及相等权数观测值的办法是，定义一个衰减因子（decay factor）常量，以便使近期的观测值拥有更大的权数。衰减因子的定义方式有很多，比较流行的是使用时间间隔（span），它可以使结果兼容于窗口大小等于时间间隔的简单移动窗口（simple moving window）函数。<br>\n",
    "\n",
    "由于指数加权统计会赋予近期的观测值更大的权数，因此相对于等权统计，它能“适应”更快的变化。"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 93,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.legend.Legend at 0x22e2ffd6ef0>"
      ]
     },
     "execution_count": 93,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "df.close.plot(style='k-',label='close')\n",
    "df.close.rolling(window=10,min_periods=0).mean().plot(style='r--',label='rolling')\n",
    "df.close.ewm(span=10).mean().plot(style='g.',label='ewm')\n",
    "plt.legend()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# 二元移动窗口函数\n",
    "有些统计运算（如相关系数和协方差）需要在两个时间序列上执行。例如，金融分析师常常对某只股票对某个参考指数（如标准普尔500指数）的相关系数感兴趣。"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 97,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.axes._subplots.AxesSubplot at 0x22e2ffb15c0>"
      ]
     },
     "execution_count": 97,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "df.close.rolling(window=10,min_periods=0).corr(df.volume).plot()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# 用户定义的移动窗口函数\n",
    "rolling_apply函数使你能够在移动窗口上应用自己设计的数组函数。唯一要求的就是：该函数要能从数组的各个片段中产生单个值（即约简）。"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 103,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.legend.Legend at 0x22e310b95f8>"
      ]
     },
     "execution_count": 103,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "df.close.plot()\n",
    "df.close.rolling(window=10,min_periods=0).apply(lambda x:x.max(),raw=True).plot()\n",
    "plt.legend()"
   ]
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.6.5"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 2
}
